Article

ISSN 0006-2979, Biochemistry (Moscow), 2026, Vol. 91, No. 1, pp. S373-S393 © Pleiades Publishing, Ltd., 2026.

Published in Russian in Uspekhi Biologicheskoi Khimii, 2026, Vol. 66, pp. 519-548.

S373

REVIEW

Pathophysiology, Biochemistry, and Molecular

Landscape of Insulin Resistance in Type 2 Diabetes

Alexander V. Vorotnikov

1,a

*, Nikita V. Podkuychenko

1,b

and Marina V.Shestakova

2,c

Institute of Experimental Cardiology, Acad. E. I. Chazov National Medical Research Center of Cardiology,

121552 Moscow, Russia

Institute of Diabetes, Acad. I. I. Dedov National Medical Research Center of Endocrinology,

117036 Moscow, Russia

e-mail: a.vorotnikov@icloud.com

e-mail: nra.fox@gmail.com

e-mail: shestakova.mv@gmail.com

Received October 30, 2025

Revised November 12, 2025

Accepted December 16, 2025

Abstract— The pathophysiology of type 2 diabetes (T2D) remains poorly understood, largely because mul-

tiple early changes are obscure as they evolve during prolonged period of prediabetes. These changes are

interconnected, involve feedback loops, and gradually develop in tissue-specific manner, ultimately leading

to manifestation as overt diabetes. Insulin resistance (IR) and pancreatic β-cell dysfunction are regarded

as central events driven by lipotoxicity and glucotoxicity. Understanding molecular mechanisms of their

causes and consequences is essential for developing effective preventive and therapeutic strategies for T2D.

This review describes the evolution of current perspectives on T2D pathophysiology, examines the mecha-

nistic roles of lipotoxicity and glucotoxicity, and integrates current concepts on the molecular basis of IR.

The hypotheses on the early events in prediabetes and potential role of IR in their progression toward

overt T2D are discussed. A deeper understanding of T2D as a metabolic disease of biochemical origin may

provide new insights into T2D prevention and major associated mortality risks, including cardiovascular

complications and cancer.

DOI: 10.1134/S0006297925604198

Keywords: type  2  diabetes, prediabetes, insulin  resistance, lipotoxicity, glucotoxicity, insulin  signaling,

phosphoproteome

* To whom correspondence should be addressed.

SECTION 1. INTRODUCTION:

THE WALK OF LIFE

Diabetes is a major socially significant non-com-

municable disease with epidemic-level prevalence

[1, 2]. Type  2 diabetes (T2D) accounts for 80-95%

of all diabetes cases across various populations and

exceeds 92% in the Russian Federation. The mortal-

ity rate in T2D is driven by comorbidities, such as

cardiovascular diseases (~50%) and, to a lesser ex-

tent, cancer (~10%)  [2]. As a metabolic disorder, T2D

highlights the central role of metabolic dysregulation

in the development of the most prevalent chronic

diseases.

The pathophysiology of T2D, defined as a se-

quence of metabolic alterations occurring during

its development, includes a prolonged period of

prediabetes that ultimately progresses to the overt

disease (Fig.  1). In its advanced stages, T2D is char-

acterized by hyperglycemia and impaired insulin

secretion, thus resembling type  1 diabetes (T1D).

However, the critical metabolic disturbances arise

much earlier, during prediabetes. In most cases, they

are marked by dyslipidemia, including obesity, el-

evated triacylglycerol (TAG) levels in adipose tissue

and the blood lipoproteins, increased plasma levels

of free fatty acids (FFA), and ectopic lipid deposi-

tion in peripheral tissues. These changes are con-

sidered major predisposing factors, whereas insulin

resistance (IR) is regarded as the principal predictor

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Fig. 1. Trajectory of metabolic alterations and IR during the pathophysiological progression of T2D. IR emerges and pro-

gresses in parallel with early hyperinsulinemia, preceding the onset of hyperglycemia. Dashed line indicates the approximate

trajectory of total lipid burden (FFA and TAG) in tissues and plasma; shaded area on the right denotes the overt T2D stage.

and central pathophysiological feature of T2D [3-5].

IR emerges at the earliest stages of prediabetes, pro-

gressively worsens, and persists throughout advanced

T2D. Although the temporal dynamics of metabolic

parameters does not establish causality, it clearly de-

fines two pathophysiological states: lipotoxicity, driv-

en by excess lipid exposure, and glucolipotoxicity,

reflecting a contribution of hyperglycemia (Fig. 1).

Together, these trajectories support the notion that

hyperglycemia is critical for the final β-cell defects

that culminate in overt T2D.

IR is defined as a reduced responsiveness of insu-

lin-dependent tissues to insulin. As IR develops, insu-

lin progressively loses its ability to stimulate glucose

uptake in skeletal muscle, suppress hepatic glucose

production, and, as generally assumed, inhibit lipoly-

sis in adipose tissue. Pancreatic β-cells are thought

to compensate for the diminished insulin efficacy by

increasing insulin secretion, resulting in compensa-

tory hyperinsulinemia. With further progression of

prediabetes, IR and associated metabolic disturbanc-

es lead to β-cell dysfunction, impaired insulin secre-

tion, hyperglycemia, and, ultimately, manifestation of

overt T2D (Fig.  1). However, the mechanistic inter-

play and temporal sequence of these events remain

incompletely understood. Long-standing questions re-

garding which event arises first and what drives its

emergence, continue to be debated. Answering these

questions may help identify effective strategies for

disease prevention and therapy.

A major challenge in understanding IR is its het-

erogeneous onset across different organs. According

to the accepted paradigm, IR initially develops in

skeletal muscle [3, 4], but the following sequence of

events remains unclear. Clinically, hepatic steatosis

accompanied by pronounced hepatic IR (non-alcohol-

ic fatty liver disease, NAFLD) often precedes the onset

of T2D and is thought to result from IR in adipose

tissue, increased lipolysis, and elevated flux of FFA

to the liver. Current concepts state that the excess lip-

id availability is the primary driver of IR in muscle

cells, with FFA acting as the main inducers of IR  [4].

In rodents, impaired carbohydrate metabolism in ad-

ipose tissue induces IR in both muscle and liver  [6],

suggesting a potential primary role for adipose IR.

However, the underlying causes remain unclear, as

lipid-induced IR pathways described in myocytes and

hepatocytes are less applicable to adipocytes, which

are inherently adapted for lipid storage and turnover.

Chronic low-grade inflammation has been implicated

as a major contributor to adipose IR [7, 8]; however,

in rodents, high fat diet induces adipose IR before

overt inflammation becomes evident  [4]. In humans,

the situation is even less clear due to the limitations

of mechanistic interventions and reliance on obser-

vational metabolic data only. Interpretation is further

complicated by substantial inter-individual variabili-

ty, requiring large cohorts for robust conclusions.

As a result, a key unresolved question remains: is IR

a primary defect, or does it represent an adaptive

cellular response to nutrient excess and hyperinsu-

linemia [9, 10]? Without a clear answer, clinical deci-

sions are challenging, particularly regarding whether

IR should be directly targeted therapeutically and

whether insulin therapy is appropriate in T2D man-

agement [11,  12].

This review summarizes the historical mile-

stones in understanding T2D pathophysiology, key

biochemical and molecular alterations during disease

progression, and the roles of lipo- and glucotoxicity

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Fig.  2. The timeline of key discoveries in understanding T2D as a metabolic disease. Events highlighted in grey denote

the major milestones also detailed in the text. Abbreviations not included in the general list: K

ATP

channels, ATP-sensitive

 channels; RIA, insulin radioimmunoassay.

inprediabetes. It also examines the evidence on plas-

ma FFA levels as markers of prediabetes, outlines

cellular mechanisms of IR development in skeletal

muscle, and discusses potential primary drivers and

plausible scenarios of metabolic events leading to

T2D development.

SECTION 2.NATURAL HISTORY

OF TYPE 2 DIABETES: SHOW MUST GO ON

Disease history describes disease progression in

an individual over time, whereas the natural history

refers to its course in the absence of treatment. Un-

ravelling the natural history of a disease provides

insight into intrinsic mechanisms of its pathogene-

sis and helps identify the most relevant therapeutic

targets. The multifactorial etiology of diabetes may

explain its heterogeneity, including T1D, T2D, matu-

rity-onset diabetes of the young (MODY), gestational

diabetes, and other less common forms. In T2D, a

prolonged latent period of prediabetes precedes the

clinical onset of overt disease. The natural history

of T2D remains poorly characterized due to systemic

metabolic alterations that obscure individual contrib-

uting factors, their interactions, and the sequence of

pathological events. The molecular mechanisms un-

derlying the two hallmark defects, IR and β-cell dys-

function, are even less well defined. These defects

characterize, respectively, the early prediabetes and

the transition to overt diabetes and, therefore, have

a primary focus in diabetes research for decades.

Yet observational description of disease progression

alone is insufficient to trace the development of these

defects and to evaluate their contribution to the over-

all disease pathophysiology. Consequently, prevailing

hypotheses must be validated experimentally in cellu-

lar and animal models, with careful extrapolation of

findings to the human disease. The major milestones

in the development and validation of these concepts

are summarized in Fig.  2. They represent only a

small fraction of the extensive literature; below, we

address only the most essential aspects relevant to

understanding IR mechanisms.

By the end of the 19th century, Oskar Minkowski

and Joseph von Mering had already established that

the pancreas produces a factor regulating carbohy-

drate metabolism. This factor was later named in-

sulin, following the discoveries of Paul Langerhans,

who identified the pancreatic islets, and Leonid

Sobolev, who found that their function persists af-

ter pancreatic duct ligation. Building on these in-

sights, Frederick Banting developed a procedure for

insulin isolation. When working in the laboratory of

John Macleod in Toronto, Banting and Charles Best

extracted insulin, administered it to a pancreatecto-

mized dog, and saved the animal  [13]. In 1922, the

first insulin injection was administered to a human

patient, 14-year-old Leonard Thompson with diabetes.

However, this extract was poorly purified and caused

an allergic reaction. Macleod then recruited James

Collip, who optimized the purification procedure, and

the second injection was successful. The 1923 Nobel

Prize in Physiology or Medicine followed immediate-

ly. It seemed that diabetes had been cured.

However, it soon became evident that insulin was

not universally effective. In 1936, H.  Himsworth ex-

perimentally demonstrated that diabetes manifests in

two different forms: one associated with impaired in-

sulin secretion and another characterized by reduced

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Fig. 3. Original hypothesis of the glucose–fatty acid cycle by P.  Randle  [22]. Intracellular lipid handling is illustrated through

the TAG cycle, which relies on glucose to support FFA (re)esterification [18,  20]. When circulating FFA levels are high, such

as during fasting, skeletal muscle predominantly utilizes FFA for oxidation, thereby reducing glucose uptake and metabolism

(left). This increases glucose influx into adipose tissue and promotes FFA re-esterification into TAG in adipocytes (right).

As plasma FFA levels decline, FFA flux into adipose tissue decreases, FFA oxidation in muscle diminishes, and glucose

transport and metabolism are restored. Under the action of insulin (e.g., postprandially), the fluxes are reversed: FFA are

directed primarily into adipocytes, whereas glucose uptake is enhanced in myocytes. 3-PG, glycerol 3-phosphate.

tissue responsiveness to insulin  [14]. In his studies,

patients received intravenous glucose along with

insulin, followed by blood sampling. In one group,

glucose levels fell and returned to baseline, where-

as in the other, insulin had little effect and glucose

levels continued to rise. In 1959, Solomon Berson

and Rosalyn Yalow developed the radioimmunoassay

for plasma insulin, providing definitive evidence for

the existence of insulin-dependent (type  1) and insu-

lin-independent (type  2) diabetes  [15]. Since then, the

concept of diminished biological response to insulin

has been firmly established and now recognized as

insulin resistance (IR).

It has long been known that individuals with

T2D exhibit elevated plasma TAG levels and are fre-

quently obese. In the early 1950s, V.  Dole developed

a quantitative assay for plasma FFA and showed that

FFA levels vary inversely with glucose, rising during

fasting and falling after glucose ingestion, and are

elevated in obese individuals  [16]. These findings in-

dicated that adipose tissue is not merely a passive

energy reservoir but plays an active metabolic role

by temporarily storing energy as TAG and supplying

other tissues with FFA via lipolysis. G.  Reaven con-

sistently emphasized the strong association between

IR and lipid metabolism abnormalities, particular-

ly elevated plasma TAG and FFA. Although initially

met with skepticism, his idea that dysregulated lipid

metabolism is central to T2D pathogenesis has been

eventually accepted [17]. It was Reaven who coined

the term “syndrome X” [5], now known as “metabol-

ic syndrome”, which is widely recognized as a major

risk factor for both T2D and cardiovascular disease.

He believed IR to be the defining feature of metabol-

ic syndrome, while the combination of IR and β-cell

dysfunction marks the transition from prediabetes

to T2D.

Studies using fragments of adipose tissue have

revealed the TAG cycle in adipocytes, a continuous

assembly-disassembly process in which a fraction of

FFA is consistently re-esterified into TAG, even during

intensive lipolysis [18,  19]. This cycle requires energy

[19] and glucose to generate glycerol 3-phosphate, the

glycerol backbone for TAG synthesis  [20]. Current evi-

dence confirms that glucose is the principal substrate

in adipocytes [21], and that its uptake and utilization

suppress lipolysis and FFA release.

Distinct oxidative pathways for glucose and fatty

acids have been recognized since the early 20th cen-

tury, both converging at their common end-product

acetyl coenzymeA (CoA). The tricarboxylic acid (TCA)

cycle was described in 1937 by Hans Krebs and Albert

Szent-Györgyi. It was reasonable to hypothesize that

the finite capacity of the TCA cycle limits the simul-

taneous maximal oxidation of both substrates. When

both glucose and FFA are abundant, such as after a

meal, they may compete for oxidative metabolism.

This concept was formalized in 1963 by P.  Randle

[22], who integrated systemic glucose and FFA fluxes

into the unified glucose-fatty acid cycle (Fig.  3).

The Randle hypothesis was transformative, offer-

ing a novel perspective on the T2D etiology. Randle

proposed that disturbances in carbohydrate metabo-

lism may arise as a consequence of altered lipid me-

tabolism. This idea seemed counterintuitive, as the

clinical paradigm of diabetes had been almost entire-

ly glucose-centric and biochemists knew that lipids

are synthesized from carbohydrates, not the reverse.

The Randle’s seminal paper introduced this interplay

as a “biochemical syndrome” in which “interactions

between glucose and fatty-acid metabolism in mus-

cle and adipose tissue take the form of a cycle (the

glucose fatty-acid cycle), and are fundamental to the

control of glucose and fatty acid concentrations in the

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Fig. 4. Biochemical mechanisms underlying substrate competition between (a)  FFA and glucose [22,  25] and (b)  between

glucose and FFA  [26] as cellular energy substrates  [26]. a)  Excessive FFA availability drives mitochondrial accumulation of

acetyl-CoA, which inhibits pyruvate dehydrogenase (PDH) within the pyruvate dehydrogenase complex. Acetyl-CoA is also

exported to the cytosol via the citrate shuttle, where citrate inhibits phosphofructokinase  1 (PFK-1). This decreases the

glycolytic flux and leads to glucose 6-phosphate (G6P) accumulation. Elevated G6P inhibits hexokinase (HK), reducing the

transmembrane glucose gradient and limiting glucose uptake. b)  Excess glucose availability enhances glycolytic flux and

pyruvate oxidation, resulting in the mitochondrial acetyl-CoA accumulation. Cytosolic export of acetyl-CoA via the citrate

shuttle fuels malonyl-CoA synthesis and de novo lipogenesis. Malonyl-CoA inhibits carnitine palmitoyltransferase (CPT) in

the carnitine shuttle, suppressing the import of fatty acid into mitochondria and β-oxidation (β-Ox). Blue dashed arrows

denote dominant fluxes; blue solid lines represent inhibitory interactions that maintain metabolic reciprocity; black dashed

lines represent multistep glycolysis and electron transfer from β-oxidation and the TCA cycle via the electron transport

chain (ETC).

blood, and of insulin sensitivity”  [22]. This ground-

breaking work has been cited more than 4000  times

and still remains influential [23,  24].

The Randle hypothesis is founded on several

key propositions: (1)  glucose and fatty acid oxidation

are interconnected yet independent; (2)  catabolism

of fatty acid, whether derived from circulating FFA

or from intracellular TAG, suppresses glucose catab-

olism in muscle; (3)  fatty acid oxidation suppresses

insulin-stimulated glucose uptake in muscle; (4)  hor-

monal regulation modulates this balance by influ-

encing lipolysis, glucose transport, or TAG synthesis

[22, 25]. Figure  3 illustrates the first three principles,

showing that the increased availability of FFA from

the bloodstream shifts muscle metabolism from glu-

cose utilization toward fatty acid oxidation to support

ATP generation. In adipocytes, higher glucose avail-

ability promotes re-esterification of fatty acids into

TAG, thereby limiting FFA release into the circulation.

Postprandial insulin reverses the metabolic fluxes by

enhancing glucose transport into muscle and channel-

ing FFA into adipocytes. Importantly, insulin does not

suppress lipolysis in muscle cells, thereby promoting

a shift in lipid balance toward the storage in adipo-

cytes. In conditions such as obesity and diabetes, the

glucose-fatty acid cycle becomes dysregulated due to

altered availability of FFA and glucose.

Randle also proposed a biochemical mechanism

to explain the substrate competition between FFA and

glucose (Fig.  4a). This mechanism is particularly rel-

evant to skeletal muscle, the major site of postpran-

dial glucose disposal. Randle hypothesized that FFA

suppress glucose oxidation by inhibiting pyruvate

dehydrogenase (accounting for 40-60% of the effect)

and phosphofructokinase  1, contributing addition-

al 20-30%. Inhibition of the latter was predicted to

cause an accumulation of glucose 6-phosphate, which

inhibits hexokinase, thus increasing intracellular glu-

cose concentrations, reducing the transmembrane

gradient of glucose, and ultimately decreasing glucose

uptake.

The reciprocal mechanism by which glucose

suppresses fatty acid utilization had been unknown

until 1977, when D.  McGarry identified malonyl-CoA,

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the first intermediate of the de  novo synthesis of fat-

ty acid from glucose, as an inhibitor of the carnitine

shuttle that transports fatty acids into mitochondria

[26] (Fig.  4b). McGarry proposed that excessive glu-

cose, typical of individuals with IR and hyperglyce-

mia, traps fatty acids in the cytosol, where they accu-

mulate and become lipotoxic  [27]. These findings laid

the foundations for the concepts of lipo- and gluco-

toxicity (see Section  3) and their involvement in IR,

impaired metabolic flexibility, and T2D pathogenesis.

Itwas found later that plasma FFA levels change little

in obesity, prompting the emergence of the concept

of ectopic fat accumulation, which referred to inap-

propriate TAG deposition in non-adipose tissues (see

Section  4). It also became evident that FFA can affect

cells not only from the outside, but also internally,

via metabolism.

A major methodological advance came with the de-

velopment of clamp techniques by R.  DeFronzo  [28]

which enabled quantitative and minimally invasive

assessment of IR in humans and were instantly ad-

opted. In the 1990s, G.  Shulman applied these tech-

niques to test the Randle hypothesis in humans (see

Section  5). Individuals with T2D exhibited decreased

insulin-stimulated glucose uptake in skeletal muscle,

contributing to reduced whole-body glucose dispos-

al [29]. This phenotype was reproduced in healthy

subjects through lipid-heparin infusion, suggesting

a causal role of FFA. Subsequent studies in skeletal

muscle identified mechanisms involving accumula-

tion of diacylglycerol (DAG), activation of Ca

-inde-

pendent novel protein kinase  C (nPKC) isoforms, and

disruption of insulin signaling [4,  30].

At the turn of the century, an alternative perspec-

tive emerged from the studies on β-cells by R.  Unger

[10, 31, 32] and on muscle and adipose cells by

S.  Summers [33]. By that time, it had become clear

that saturated FFA, such as palmitate, are more li-

potoxic than unsaturated FFA, such as oleate. Unlike

oleate, palmitate is inefficiently incorporated into

TAG and is instead diverted into ceramide synthesis,

which induces IR and β-cell apoptosis [34]. Inhibi-

tors of key enzymes of ceramide biosynthesis (serine

palmitoyl transferase and ceramide synthase) sup-

pressed IR in myocytes and adipocytes, and protected

β-cells from apoptosis [35]. R.  Unger studied Zucker

rats, which have impaired leptin function and spon-

taneously develop obesity. He viewed these animals

as a natural model of lipotoxicity and demonstrated

that lipid overload initially stimulated β-cell prolif-

eration and insulin secretion, but eventually led to

the lipotoxic failure of β-cells  [10]. Unger proposed

that hyperinsulinemia as a primary event, while IR

is a secondary adaptive response of peripheral tis-

sues to avoid hypoglycemia, a concept that has been

developed further in subsequent studies [12, 36, 37].

Mechanisms driving increased basal insulin secre-

tion may involve FFA-induced generation of reac-

tive oxygen species and altered β-cell redox status.

Within this framework, primary hyperinsulinemia

and IR are viewed as adaptive responses aimed to

normalize circulating lipid and glucose levels under

nutrient excess [9]. Further progression of adipose IR

was thought to impair suppression of lipolysis while

preserving lipogenic activity of insulin, thereby exac-

erbating obesity and lipotoxicity [10, 11]. In β-cells,

increased lipid burden promotes ceramide accumula-

tion, oxidative stress, and impaired insulin secretion,

leading to hyperglycemia, glucolipotoxicity, and overt

T2D  [38].

Finally, the concept of impaired metabolic flexi-

bility has emerged  [39] that to a certain extent inte-

grated prior hypotheses at both cellular and whole-

body levels  [40] by applying the same principles

of reciprocal substrate and metabolite competition

originally proposed by Randle and McGarry (Fig.  4).

The dysregulation of these mechanisms, compound-

ed by altered amino acid metabolism, leads to the

mitochondrial overload and loss of ability to switch

between glucose and fatty acids as cellular fuels

[39]. Under these conditions, it is plausible that cells

adapt to chronic FFA oversupply by downregulating

insulin-stimulated glucose uptake as a protective re-

sponse. Alternatively, this may represent an adap-

tation to chronic hyperinsulinemia. Recent studies

suggest that the insulin metabolic signaling can be

selectively attenuated, while its mitogenic signaling

remains relatively preserved [41, 42] (see Section  6).

Hyperglycemic clamp. Plasma glucose is rapidly raised by intravenous glucose infusion and maintained at a target

level through continuous feedback-controlled adjustment of glucose infusion rate. Once the steady state is achieved,

the glucose infusion rate reflects the whole-body glucose disposal and metabolism at intact endogenous insulin secre-

tion. This clamp variant is used less frequently because it reflects the combined effects of IR and endogenous insulin

release.

Hyperinsulinemic-euglycemic clamp. Plasma insulin is acutely elevated by insulin infusion and then maintained at

~100  μU/ml (~0.6  nM). Plasma glucose is monitored continuously, and the glucose infusion rate is adjusted in a feed-

back-controlled manner to maintain euglycemia at the individual’s basal level. Under these conditions, the glucose

infusion rate equals the whole-body glucose disposal and therefore provides a quantitative measure of sensitivity to

exogenous insulin. This approach is more commonly used because it isolates IR without the confounding influence

of endogenous insulin secretion. Combined use of both clamp procedures allows assessment of β-cell secretory dys-

function independently of IR.

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Excessive FFA availability increases cellular de-

mand for fatty acid disposal via lipid synthesis (phos-

pholipids, sphingolipids, and ceramides), mitochondri-

al β-oxidation for ATP generation, or storage as TAG

in lipid droplets. Overloading these pathways may

induce endoplasmic reticulum (ER) stress, oxidative

stress, or lipotoxicity, respectively, depending on the

susceptibility of specific cell type. For example, when

ATP consumption is low and ATP tends to accumu-

late, the FFA flux shifts toward lipid storage and

synthesis, inducing formation of DAG and ceramides.

The failure to adequately metabolize FFA may trigger

lipotoxicity once the buffering capacity of FFA-bind-

ing proteins and/or pool of free CoA are exhaust-

ed. Depending on the cell type, impaired metabolic

flexibility may reflect not only the IR itself, but also

ER stress, mitochondrial overload, reduced electron

transport chain activity, or increased oxidative stress

[43,  44].

Despite significant progress, the mechanisms un-

derlying metabolic dysfunction in IR and T2D remain

poorly understood. As a result, a unified theory that

conclusively delineates the sequence of pathogenic

events in prediabetes or identifies definitive therapeu-

tic targets has yet to emerge (see Section  7). Although

disturbed lipid metabolism is widely recognized as a

central contributor, understanding its complex conse-

quences continues to be a major challenge.

SECTION 3.LIPOTOXICITY AND GLUCOTOXICITY:

DOES THE TAIL WAG THE DOG?

The term lipotoxicity was introduced by R.  Unger

[31] in relation to the impaired insulin secretion by

β-cells. The concept has been later expanded to other

tissues, highlighting its broader systemic impact [45],

including impaired leptin signaling  [32]. Currently,

lipotoxicity is understood as a series of interrelated

events triggered by dysregulated lipid metabolism

and excessive FFA action.

Dietary lipids enter the lymphatic system as

chylomicrons and subsequently reach the systemic

circulation through the superior vena cava. Lipopro-

tein lipase (LPL) located on the surface of vascular

endothelial cells, hydrolyzes chylomicron TAG to re-

lease FFA. FFA cross the endothelial barrier with the

assistance of albumin, which transiently binds them

to mitigate acute cytotoxicity of unbound FFA [46].

High LPL activity markedly increases local FFA lev-

els, leading to FFA “spillover,” which may account for

up to one third of circulating FFA [47]. Together with

chylomicron remnants, these FFA eventually reach

the liver, where they are re-esterified into TAG and

packaged into very-low-density lipoproteins (VLDLs).

In the postprandial state, the liver also receives FFA

mobilized from adipose tissue and incorporates them

into VLDL TAG. As VLDLs circulate, they gradually

release FFA to peripheral tissues and are convert-

ed into intermediate- and low-density lipoproteins.

In obesity, lipodystrophy, and conditions involving

limited storage capacity or inflammation in adipose

tissue, the plasma levels of circulating lipoproteins

increase, reflecting increased lipid burden, enhanced

lipid flux to peripheral tissues, and increased risk of

FFA excess and lipotoxicity. Chronic expose to elevat-

ed FFA promotes ectopic lipid deposition in non-ad-

ipose organs. In the liver, this manifests as NAFDL,

while in skeletal muscle, ectopic lipids serve as en-

dogenous sources of FFA, which blunt insulin sensi-

tivity, reduce glucose uptake [4, 27, 30], and suppress

glucose catabolism [22,  25].

Lipotoxicity is defined as deleterious effects of

FFA on cells. Circulating amphipathic FFA are inher-

ently cytotoxic and are rapidly sequestered by serum

albumin. Each albumin molecule can bind up to sev-

en FFA, including three with high affinity (binding

constants in the micromolar range)  [48]. Although

plasma FFA concentrations vary considerably, they

rarely exceed 2  mM (see Section  4), while normal al-

bumin levels (40-50  g/L) correspond to ~0.7  mM. Thus,

under physiological conditions, albumin is in excess

and effectively buffers FFA. However, albumin also

transports other ligands, and its levels decline with

aging and inflammation. Furthermore, glycation re-

duces albumin’s binding capacity  [49] and promotes

expression of inflammatory cytokines in muscle cells

[50]. Therefore, elevated levels of glycated albumin

in hyperglycemia may increase susceptibility to lipo-

toxicity and could serve as a potential biomarker for

T2D risk [51,  52].

Modeling lipotoxicity requires careful consid-

eration because of the risk of direct FFA toxicity.

Under such conditions, the membrane compartment,

including ion channels, transporters, receptors, and

their proximal targets, is expected to be particular-

ly vulnerable. In  vitro, FFA are typically delivered to

cells in a complex with albumin, whereas in  vivo, FFA

levels are increased by infusing an emulsion of lipids

(TAG) together with heparin to activate LPL. In both

settings, the FFA-to-albumin ratio is critical[53]. Once

it exceeds a threshold of ~3  mol FFA per mol of al-

bumin, the concentration of unbound FFA approach-

es the solubility limit (10-20  nM), markedly increasing

the risk of direct lipotoxicity. Although in vivo this

ratio rarely exceeds 2  mol FFA per mol albumin, it

may rise substantially in severe obesity, aging, hyper-

glycemia, or due to extensive albumin glycation.

Metabolic lipotoxicity arises from the intracel-

lular accumulation of excessive FFA and typically

occurs when one of the four major FFA-processing

systems becomes limited: (1)  the buffering capacity

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BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

of fatty acid-binding proteins (FABPs) that seques-

ter intracellular FFA  [54]; (2)  the availability of free

coenzyme A required for FFA activation, retention,

and subsequent metabolic processing or carnitine

[55]; (3)  the capacity to synthesize and expand lipid

droplets for extra TAG storage  [56]; (4)  mitochondrial

β-oxidation capacity  [39]. The availability of CoA is

limited by its cytosolic concentration (~0.1-0.15  mM)

[55]. The efficiency of lipid droplets in sequestering

FFA into TAG depends on the cell type. For instance,

skeletal muscle cells express low levels of fatty acid

synthase and generate lipid droplets poorly, except

in endurance-trained athletes, whose myocytes ac-

cumulate substantial TAG and droplets, a phenom-

enon known as the “athlete’s paradox”  [57]. Thus,

mitochondrial oxidation serves as the primary route

of FFA disposal in muscle cells. By contrast, adipo-

cytes possess highly developed lipogenic machinery

and active TAG cycling. White adipocytes oxidize FFA

poorly due to low expression of carnitine palmito-

yltransferase (CPT-I)  [58], whereas beige and brown

adipocytes express CPT-I and actively oxidize FFA to

maintain lipid balance and support thermogenesis

[59]. The term “toxicity” can be misleading, as it does

not differentiate between acute physical damage and

chronic metabolic reprogramming accompanied by

adaptive cell responses. In essence, these metabolic

shifts are reversible at both cellular and whole-body

levels. A similar rationale applies to glucotoxicity,

which refers to detrimental effects of sustained hy-

perglycemia  [60].

The concept of glucotoxicity also originated in

relation to β-cells  [31]. Because the vascular endo-

thelium in the pancreas is fenestrated, even modest

elevations in plasma glucose rapidly stimulate insulin

secretion. This insulin promotes glucose disposal pri-

marily by skeletal muscles, which accounts for ~80%

of glucose clearance from the circulation. Chronic hy-

perglycemia in  vivo or prolonged exposure of isolated

islets to glucose in  vitro impair insulin secretion by

β-cells, providing the basis for the glucotoxicity con-

cept [60,  61]. Experimental diabetes induced by par-

tial pancreatectomy in rats primarily resulted from

impaired insulin secretion  [62]. Treatment with phlo-

rizin (an inhibitor of renal glucose reabsorption and

a prototype of modern SGLT2 inhibitors) normalized

blood glucose without affecting other blood param-

eters in these animals. These findings indicate that

glycemic control is essential not only for reducing

vascular risks, but also for reversing glucotoxic ef-

fects of hyperglycemia on β-cells and abating IR in

skeletal muscle and liver  [60].

Lipotoxicity is likely to precede glucotoxicity in

T2D. However, this does not exclude the possibility

that hyperglycemia can exacerbate the lipotoxic ef-

fects. As noted above, β-cells are particularly vul-

nerable to glucolipotoxicity  [38]. Glycation reduces

albumin’s affinity for FFA  [48], thereby increasing

the risk of direct lipotoxicity. Because vascular en-

dothelium in the liver and pancreas is fenestrated,

hepatocytes and β-cells are directly exposed to albu-

min-bound FFA. They sense elevated FFA in complex

with FABP4, originating from adipose tissue  [63] or

vascular endothelium  [64], and respond by increas-

ing glucose output (hepatocytes) or insulin secretion

(β-cells). Platelets, frequently activated in metabolic

disorders, increase phospholipid hydrolysis to release

FFA that stimulate insulin secretion by β-cells  [65].

This unexpected finding suggests another FFA-medi-

ated mechanism of primary hyperinsulinemia induc-

tion occurring even before systemic FFA elevation or

the onset of glucotoxicity.

The mechanism linking glucotoxicity and lipotox-

icity remains poorly understood. It may involve accu-

mulation of glucose-derived metabolic intermediates

[21, 66, 67], some of which fuel de  novo lipogenesis

and TAG synthesis, thereby promoting ectopic fat ac-

cumulation and increasing susceptibility to lipotox-

icity. Collectively, these changes converge into glu-

colipotoxicity. Alternatively, lipotoxicity may develop

more insidiously, through the metabolic scenario, be-

coming clinically evident once glucotoxicity emerges.

Perhaps, only in cases of severe obesity (body mass

index, BMI  >  35) lipotoxicity can occur independently,

potentially as a result of direct FFA toxicity, when the

buffering capacity of blood plasma proteins and he-

patic mechanisms are exhausted, thereby increasing

the mortality risk [68] (see below).

SECTION 4.OBESITY,

FFA PLASMA LEVELS, AND ECTOPIC LIPIDS:

OUTSIDE LOOKING INSIDE

Although T2D develops only in a subset of obese

individuals, the population prevalence of obesity and

T2D is comparable  [69]. Obesity is strongly associat-

ed with IR and is considered a major risk factor for

T2D [5,  17]. Early studies reported elevated plasma

FFA in individuals with T2D [22,  70,  71]; several stud-

ies also found increased plasma FFA levels in people

with obesity but without diabetes [16,  72,  73]. Cases

of elevated FFA in the absence of obesity, yet accom-

panied by abnormalities in carbohydrate metabolism

[71], may reflect genetic factors (e.g., MODY) or insuf-

ficient adipose storage capacity to remove FFA from

the circulation, as observed in lipodystrophy [74].

These findings have raised questions about whether

plasma FFA levels might be indicative of IR.

Detailed analysis of diurnal FFA profiles re-

vealed no significant differences between individuals

withand without obesity [74,  75]. However, increased

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lipoprotein-TAG and hyperinsulinemia in subjects

with obesity indicated the presence of IR. In this

study, small groups of participants (n  =  10 each) were

stratified by body mass index (BMI 27-32 vs. 19-25).

Across all participants, the plasma levels of FFA var-

ied substantially throughout the day, largely depend-

ing on the food intake and insulin levels, but were

essentially independent on the obesity status. These

findings prompted the authors to question whether

FFA alone could account for IR and adverse metabol-

ic consequences of obesity [74,  76]. Further support

came from an extended analysis of blood samples

from 1,591 individuals registered in the Oxford Bio-

bank, which confirmed the absence of direct associ-

ation between the BMI and fasting FFA levels [76].

By that time, results from the large Paris Prospective

Study were also available (n  =  5790; BMI  <  33) [77].

Retrospective analysis of these data found no signifi-

cant differences in FFA plasma levels across individ-

uals without or with obesity of varying degrees [77].

The Stockholm study, which included ~4000 in-

dividuals provided further insights into relationship

between obesity and circulating FFA [78]. Obesity

was defined as BMI  ≥  30, although no upper BMI

limit was specified. Obese individuals exhibited small

but statistically significantly higher FFA plasma lev-

els (0.71  ±  0.23  mM) compared to non-obese subjects

(0.57  ±  0.23  mM). Similar differences were observed

for plasma glycerol, a marker of adipose tissue lip-

olysis. Notably, no difference in FFA levels was found

between individuals with or without IR.

A subsequent study examined healthy volunteers

(n  =  48), individuals with prediabetes (n  =  20), and pa-

tients with either newly diagnosed or controlled T2D

(n  =  48 per group) [52]. Median plasma FFA levels in

T2D patients were more than 3-fold higher than in

healthy controls (~1.1  mM vs. ~0.3  mM, respectively),

yet no definitive FFA threshold distinguishing healthy

individuals from diabetic subjects was observed.

Apilot prospective analysis revealed that in individu-

als with prediabetes who later progressed to T2D, FFA

levels steadily increased over four years. These find-

ings suggest that plasma FFA rise during prediabetes

and become significantly elevated in T2D. Notably,

the predictive value of FFA levels improved substan-

tially when combined with the degree of albumin gly-

cation [52]. Glycation-induced reduction in albumin’s

affinity for FFA may explain relatively weak lipotoxic

effects in prediabetes, which later amplify as obesity,

IR, hyperglycemia converge during T2D progression.

More recently, a large-scale Copenhagen popula-

tion study was conducted that involved ~110,000 in-

dividuals. Metabolic profiling of blood samples was

performed for nearly 30,000 participants, and mortal-

ity outcomes (all-cause, cancer-related, cardiovascular,

and other causes) have been tracked over the follow-

ing 10-11 years [68]. A distinctive aspect of this study

was inclusion of individuals with BMI  >  35, whereas

earlier studies either rarely included participants

with BMI exceeding 32-33 [76,  77], or did not clearly

report the proportion of participants with BMI  >  35

[78]. Thus, the Copenhagen study provided unique

insights into metabolic features in individuals with

severe obesity.

The study demonstrated that plasma glycerol

levels increased proportionally to BMI and continued

to rise in individuals with BMI  >  35 [68]. Similar to

FFA, glycerol served as a marker of adipose tissue

lipolysis, indirectly reflecting FFA release, which was

not directly measured. In contrast, plasma lipopro-

tein-TAG increased only up to BMI of 35-37, after

which they plateaued, and declined at BMI  >  40-42

[68]. This pattern suggests that lipoprotein buffer-

ing capacity becomes exhausted at BMI  ~  35, beyond

which the liver can no longer sufficiently sequester

FFA into lipoprotein TAG. Accordingly, 3-hydroxybu-

tyrate plasma levels started to increase exponential-

ly at BMI 33-35, indicating a metabolic shift toward

channeling excess FFA into hepatic ketogenesis.

Both elevated glycerol and 3-hydroxybutyrate

were strongly associated with mortality  [68]. The

hazard ratio surpassed the significance threshold and

continued to rise with increasing 3-hydroxybutyrate

levels at BMI  ≥  35. These findings suggest that FFA

may become increasingly lipotoxic in severe obesity

(BMI  >  35). Moreover, the mortality risk correlated

directly with plasma glycerol levels across their en-

tire range, highlighting hepatic dysfunction as an im-

portant mortality risk, which manifests as impaired

hepatic clearance of glycerol and FFA generated by

high adipocyte lipolysis.

Collectively, the studies of plasma levels of FFA,

metabolites of adipose-tissue lipolysis, and their he-

patic products across different degrees of obesity

suggest that the buffering capacity of circulating li-

poproteins is generally sufficient to prevent overt li-

potoxicity across a broad BMI range. However, this

protective mechanism deteriorates when BMI exceeds

~35-37. This likely explains why earlier studies in in-

dividuals with BMI  <  35 reported little or no associa-

tion between plasma FFA levels and BMI [74-78]. The

expected relationship is likely to emerge in severe

obesity (BMI  >  35-37), when the storage capacity of

lipoproteins and, possibly, adipocytes, is exhausted,

leading to marked FFA elevation that increases the

risks of all-cause, cardiovascular, and cancer mortal-

ity [68].

In summary, individuals with T2D and IR ex-

hibit substantially higher FFA plasma levels than

healthy subjects. In contrast, those with mild-to-mod-

erate obesity (up to BMI  ~  33-35) typically maintain

plasma FFA within the normal range (<  ~  0.75  mM),

VOROTNIKOV et al.S382

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

regardless of IR status. This raises an important ques-

tion: how can FFA drive IR in prediabetes if their

plasma levels remain normal? A plausible explana-

tion is that chronic accumulation of FFA in periph-

eral tissues induces local IR [30,  74], effectively shift-

ing the primary site of FFA action from extracellular

(plasma-derived) to intracellular (ectopic fat).

SECTION 5. SKELETAL MUSCLE

INSULIN RESISTANCE: WHO IS TO BLAME?

Tissue-specific mechanisms of IR have been re-

cently reviewed in  [4]. The studies of these mech-

anisms have shaped a concept of lipid-induced IR

etiology across distinct tissues  [79]. However, closer

examination suggests that the mechanisms driving

skeletal muscle IR may be more complex than ini-

tially assumed. A key challenge is that metabolic ab-

normalities observed in T2D individuals reflect an

end-stage phenotype that develops gradually over a

prolonged period of prediabetes. Because long-term

interventional studies in healthy subjects are not fea-

sible, short-term approaches have been used to infer

causality. Few-hour hyperinsulinemic clamp proto-

cols and lipid-heparin infusions have been employed

in healthy volunteers to assess the acute effects of

elevated plasma FFA. An inherent limitation of this

approach is that acute FFA elevations may produce

rapid direct effects on proximal targets, such as those

near the plasma membrane, without fully recapitu-

lating chronic metabolic remodeling. Nonetheless,

the similarity between the findings from lipid infu-

sion studies in healthy subjects and observations in

T2D patients, who had elevated FFA without lipid in-

fusion, suggested a common mechanism for lipid-in-

duced IR in humans. Apparently, this rationale has

guided the seminal studies by G.  Shulman, G.  Boden,

and colleagues in the 1990s, which have shaped cur-

rent understanding of lipid-induced IR.

G.  Shulman employed

P and

C isotopes along

with magnetic resonance spectroscopy (MRS) to quan-

tify glucose 6-phosphate (G6P) in skeletal muscle in

healthy individuals and patients with T2D. Contrary

to the predictions of the Randle hypothesis, intracel-

lular G6P levels were not elevated in T2D; instead,

they were markedly reduced [80]. Moreover, insu-

lin-stimulated glycogen synthesis, the primary route

of glucose disposal in skeletal muscle [81], was no-

ticeably impaired in T2D. These observations indicat-

ed that glucose uptake by myocytes is defective at a

step preceding G6P formation, implicating abnormali-

ties in either glucose transport or hexokinase activity

(Fig.  4a).

To assess whether glucose transport is impaired,

open microdialysis technique was used to quantify

intracellular glucose and its transmembrane gradi-

ents in skeletal muscle in  vivo. This technique had

been developed to measure interstitial glucose con-

centrations in human adipose tissue during a clamp

[82]. Later, it was combined with isotopic tracers and

MRS, first validated in rats [83], and then applied in

humans [84]. In rats, intracellular glucose amounted

to <1  mM under hyperglycemia (20  mM) without in-

sulin, when glucose uptake by cells was low, and to

<0.1  mM under 10  mM glucose with hyperinsulinemia

(1200  pM)  [83]. Human data showed slightly different

values, but followed the same the principle: intracel-

lular glucose remained far below extracellular lev-

els during hyperglycemic (10  mM) hyperinsulinemic

(50-60  µU/mL, or 310-370  pM) clamp [84]. In healthy

lean individuals (BMI  ~  22), intracellular glucose was

~0.1  mM, whereas in T2D patients (BMI  ~  31), it was

~0.24  mM, which was still ~25-fold lower than would

be expected if hexokinase were inhibited. The whole-

body glucose disposal in these patients was ~5-fold

lower, accompanied by reduction in both glycogen

synthesis and G6P levels.

These results demonstrate that intracellular glu-

cose concentrations are consistently much lower than

the extracellular levels, and that insulin further re-

duces intracellular glucose concentrations several-fold

[83]. This implies that insulin stimulates intracellular

glucose utilization. Although not explicitly discussed

by the original authors, these data suggest that insu-

lin regulates not only glucose transport but also in-

tracellular glucose metabolism. That is, glucose influx

into a cell may not be the primary rate-limiting step

for metabolism. Instead, increased intracellular glu-

cose consumption may itself enhance glucose influx,

as intracellular utilization begins to outpace extracel-

lular availability of glucose. This passive metabolic

reinforcement by the “pull” mechanism may be com-

plemented by the active “push” mechanism, whereby

insulin drives the translocation of glucose transport-

ers to the plasma membrane. To determine which

mechanism predominates, it is necessary to find out

which responds earlier to insulin stimulation. Recent

metabolomic studies in cultured 3T3-L1 adipocytes

[21], which share the canonical mechanism of insu-

lin-dependent glucose uptake with skeletal muscle,

have addressed this question. These studies showed

that insulin activates intracellular glucose utilization

before increasing glucose entry into the cells [21].

Specifically, insulin first rapidly stimulated glycolysis,

lactate production, and the pentose phosphate path-

way, while glycogen synthesis increased independent-

ly of glucose influx [85]. Although the mechanism of

this rapid metabolic action of insulin remains unclear,

it also involves triggering of synthesis of fatty acids

and glycerol 3-phosphate required for TAG formation

(Fig.  3), with increased glucose influx occurring only

INSULIN RESISTANCE IN T2D PATHOPHYSIOLOGY S383

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

subsequently [86]. These results are in line with ob-

servations that intracellular glucose concentration in

skeletal muscle of T2D patients are elevated, rather

than reduced compared to healthy controls [84], sug-

gesting that the defects in T2D may involve not only

glucose uptake, but also dysregulation of intracellular

glucose metabolism. Notably, muscle glycogen content

is reduced in T2D subjects [87], which rules out sat-

uration of glycogen stores as the cause of increased

glucose concentrations, but does not exclude the pos-

sibility that glucose catabolism is impaired in T2D.

This logic required examination of the effects of

circulating FFA on glucose transport and metabolism

in skeletal muscle of healthy humans in  vivo. The ear-

liest such studies were likely conducted by Boden and

colleagues [88]. They showed that lipids rapidly (with-

in an hour) replaced glucose as oxidation substrates

in the vastus lateralis muscle, consistent with the

Randle hypothesis. Acetyl-CoA levels increased more

than 4-fold within 6  h of lipid infusion compared

with the no-infusion control, supporting proposed

inhibition of pyruvate dehydrogenase by excess FFA

(Fig.  4a). In addition, following lipid infusion the gly-

cogen synthase activity declined to basal levels, simi-

lar to those observed in the absence of insulin, indi-

cating a loss of insulin-stimulated glycogen synthesis

in response to FFA. The whole-body glucose disposal

declined within 3-4  h of lipid infusion, although G6P

and citrate levels in muscle remained unaltered at

6 hours. Notably, a 2-hour lipid infusion produced a

comparable delay in the suppression of glucose up-

take, which began to recover ~3  h after the end of

infusion [87]. Together, these findings suggest that the

classical Randle mechanism operates only transiently

following increase in plasma FFA levels, after which

additional mechanisms may take over.

Boden and colleagues then examined the dose-re-

sponse relationship between circulating FFA and in-

sulin action [89]. At low plasma FFA concentrations

(0.05  mM), insulin-stimulated whole-body glucose dis-

posal and glycogen synthesis in skeletal muscle were

not affected. Physiological FFA levels (~0.55  mM, see

[76  78]) caused detectable metabolic impairment:

insulin increased glucose uptake only during the

first 3  h of the clamp and failed to stimulate glyco-

gen synthesis, whereas G6P levels declined. At higher

FFA concentrations (0.75  mM), insulin no longer stim-

ulated glucose uptake or glycogen synthesis, although

intracellular G6P was transiently elevated between 4

and 6  h of the clamp. Taken together with the earlier

findings [88], these results suggested that the Randle

cycle may operate transiently and in a context-depen-

dent manner following substantial elevation in plas-

ma FFA. However, FFA also appear to act through

additional mechanisms, inhibiting glucose utilization

without accumulation of intracellular G6P.

Resolving these mechanisms required accurate

in  vivo quantification of intracellular G6P. Conven-

tional biochemical assays performed in tissue ho-

mogenates are limited and can yield imprecise re-

sults [90]. To overcome these limitations and enable

time-resolved quantification of G6P in human muscle

in  vivo, Shulman and colleagues combined

P- and

C-MRS and hyperinsulinemic euglycemic clamps

[90]. Lipid infusion in healthy volunteers increased

plasma FFA to ~2  mM and was shortly followed by a

decline in glucose oxidation. After some delay, both

glucose influx into muscle and glycogen synthesis

decreased. Intracellular G6P concentrations increased

only within the first hour and subsequently fell be-

low the control values, consistent with a biphasic

response: an initial transient Randle effect followed

by impaired insulin-dependent glucose uptake and/or

reduced G6P formation due to hexokinase inhibition.

To determine whether FFA selectively impair

glucose transport, the open microdialysis technique

previously validated in animals [83] and in patients

with T2D [84], was combined with MRS and eugly-

cemic (5  mM) hyperinsulinemic (400  pM) clamp and

muscle biopsies in healthy volunteers[91]. Lipid-hep-

arin infusion raised FFA concentration to ~1.8  mM,

whereas glycerol infusion (control) reduced FFA from

~0.5  mM to ~0.1  mM. In the lipid infusion group, glu-

cose uptake, glucose oxidation, and glycogen synthe-

sis were markedly reduced throughout the 6-hour

clamp, while G6P levels remained largely unaltered.

Overall, these responses resembled previous observa-

tions in patients with T2D [84], supporting the notion

that these metabolic defects were driven by excess

FFA. Intracellular glucose concentrations measured

2-4  h into the clamp were markedly lower in the lip-

id-infusion group (0.04  mM) than in the control group

(0.25  mM)  [91]. On the one hand, this pattern indi-

cated that the Randle mechanism was not operative

under these conditions, as intracellular glucose failed

to accumulate. On the other hand, these values con-

trasted with earlier measurements in healthy subjects

(~0.1  mM) with that in patients with T2D (~0.24  mM)

[84]. This discrepancy suggests that chronic IR in T2D

may involve additional defects in glucose catabolism

that weaken the intracellular “pull” mechanism of

glucose influx, similar to mechanisms described in

adipocytes [21,  86]. Whether similar defects occur in

human skeletal muscle and contribute to disease pro-

gression remains unresolved.

In summary, these complex in  vivo studies demon-

strated that skeletal muscle glucose transport is sup-

pressed in a lipid-dependent manner and that the

Randle cycle may operate only transiently at high

FFA levels. Although these findings revealed acute,

and possibly direct, lipotoxic effects of FFA, it is like-

ly that additional metabolic mechanisms contribute

VOROTNIKOV et al.S384

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

to impaired glucose utilization in skeletal muscle in

response to chronic ectopic lipid accumulation in pre-

diabetes. Many of these mechanisms are discussed

by the authors themselves [4].

SECTION 6. MOLECULAR LANDSCAPE

OF INSULIN RESISTANCE:

WHAT IS TO BE DONE?

Because lipid infusion impairs insulin-dependent

glucose uptake in skeletal muscle, it was logical to

propose that the primary targets of FFA may reside

in the plasma membrane compartment. Indeed, West-

ern blot analysis of muscle biopsies from healthy vol-

unteers demonstrated that lipid infusion blunted in-

sulin-induced activation of phosphoinositide 3-kinase

(PI3K), a principal intracellular effector of insulin

action  [91]. These observations led to the hypothe-

sis, and subsequent demonstration, that FFA act by

increasing intracellular levels of DAG, which in turn

activates a subset of Ca

-independent nPKC isoforms

(Fig.  5). Activated nPKCs phosphorylate insulin re-

ceptor substrate (IRS) proteins, the immediate down-

stream targets of the insulin receptor. This serine-di-

rected phosphorylation of IRS proteins blocks insulin

signaling via PI3K and Akt kinase (protein kinase

B/AKT1-3). Subsequent studies identified similar IRS

inactivation via serine phosphorylation in other cell

types [8,  17]. This mechanism is now recognized as a

part of a large regulatory network in which multiple

serine/threonine kinases phosphorylate distinct ser-

ine residues in IRS proteins to attenuate various as-

pects of their function [42, 92, 93]. Collectively, these

findings established the concept of lipid-induced IR,

whereby elevated FFA suppress insulin signaling and

glucose uptake in peripheral tissues [30,  79].

In addition to lipid-induced mechanisms that

impair insulin signaling, several other pathways may

contribute to FFA-induced metabolic dysfunction.

Among these, ceramide-mediated mechanism has at-

tracted particular attention  [35]. Ceramides are syn-

thesized from palmitate, the most abundant saturat-

ed FFA in humans  [38]. Ceramides attenuate insulin

signaling and exert independent metabolic effects

[33-35]. With respect to insulin signaling, ceramides

inhibit insulin action by activating Akt phosphatase or

by preventing Akt translocation to the plasma mem-

brane, thereby interrupting signaling downstream of

the insulin receptor and IRS proteins. Independent-

ly of insulin signaling, ceramides promote FFA

channeling into TAG in adipocytes and hepatocytes,

Fig.  5. Signaling mechanisms of insulin resistance. The scheme illustrates the major branches of insulin signaling, includ-

ing the mitogenic arm (pink) and the metabolic arm (dark and light blue). The lower panel shows the major metabolic

processes regulated by insulin: lipid synthesis in the ER, protein synthesis on the ribosomes of the rough ER, glycogen

synthesis in the cytoplasm, and mitochondrial substrate oxidation for ATP production. Lipid metabolism and the TAG cycle

are shown in green and include TAG, DAG, FFA, and ceramides (Cer). Black blunt-ended arrows indicate inhibitory signals

that attenuate insulin signaling from insulin receptors and involve nPKCs, insulin-independent inflammatory protein kinases

IKK (IkB kinase) and JNK (c-Jun N-terminal kinase), and ceramides. TSC1/2 (tuberous sclerosis proteins  1 and  2, GTPase-

activating proteins for Rheb GTPase) and PRAS40 (proline-rich Akt substrate of 40  kDa, also known as AKT1S1) function

as independent Akt effectors.

INSULIN RESISTANCE IN T2D PATHOPHYSIOLOGY S385

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

impair mitochondrial function, and suppress respira-

tory chain activity [44]. Importantly, IR mechanisms

that do not directly involve canonical insulin signal-

ing are receiving increasing attention. In addition to

mitochondrial dysfunction, these include ER stress, ac-

cumulation of acyl-carnitines, and oxidative stress [4,

9]. Importantly, in endothelial cells, excessive FFA in-

duce oxidative stress and cell death without affecting

the IRS-Akt signaling, at least while cells remain via-

ble for several days [94]. This observation highlights

that FFA do not invariably act through direct lipotox-

icity, but may also exert broader metabolic effects.

The insulin-signaling network coordinates a

wide array of cellular processes that can be broadly

grouped into mitogenic and metabolic branches [42]

(Fig.  5). The metabolic arm is structurally heteroge-

neous and regulates carbohydrate metabolism as well

as anabolic programs of lipid and protein synthesis

via mTORC1 (mechanistic target of rapamycin com-

plex  1). Accumulating evidence suggests that in IR

and/or T2D, signaling defects arise in the metabolic

branch, specifically at distal post-receptor nodes that

are directly linked to the glucose transport control

[41, 95-98]. One proposed explanation is that this may

be due to an excess (“spareness”) of the key signal-

ing molecules, such as Akt, which may be unevenly

distributed across downstream pathways [41]. Conse-

quently, partial attenuation of Akt activity in IR or

T2D may disproportionately impair the glucose-trans-

port arm of insulin signaling. However, direct in  vivo

evidence has been lacking until recently, especially

in the context of physiological postprandial response.

We addressed this gap by performing phosphopro-

teomic  [99] and transcriptomic  [100] profiling of skel-

etal muscle from healthy individuals and obese pa-

tients with T2D before and one hour after ingestion

of a mixed meal adjusted for body weight. In healthy

participants, plasma glucose and insulin peaked at

~30  min with glucose returning to baseline within

an hour  [101]. A weaker, prolonged second phase of

insulin secretion was observed, that resolved by~3  h,

indicating that under physiological conditions, insu-

lin action is largely completed within an hour, en-

suring efficient clearance of excess glucose from the

circulation. In contrast, obese T2D patients exhibited

markedly higher glucose and insulin levels, which

remained near maximum for at least 2  h postpran-

dially and did not return to baseline even after 3  h.

Fasting glucose and insulin were also elevated rela-

tive to healthy donors, consistent with chronic IR and

uncompensated hyperglycemia.

Phosphoproteomic profiling of the vastus later-

alis muscle revealed similar postprandial signaling

patterns in healthy donors and obese patients with

T2D. In healthy muscle, insulin activated virtual-

ly all signaling branches, including metabolic [Akt,

TBC1D4 (GAP for Rab GTPase, also known as AS160),

GSK3β (glycogen synthase kinase-3α/β), mTORC1, Cbl/

TC10 (ubiquitin ligase Cbl/GTP-binding protein TC10)]

and mitogenic (extracellular regulated MAP kinases

Erk1/2) arms [99]. In T2D muscle, insulin signaling

was attenuated, but not completely abolished. Con-

sistently, transcriptomic analysis showed no major

differences between the groups [100], suggesting at

least partially preserved insulin responsiveness in

T2D with obesity. Western blot analysis confirmed

significantly increased postprandial phosphorylation

of Akt in patients with T2D relative to fasting lev-

els, whereas TBC1D4 phosphorylation remained un-

changed. Notably, insulin failed to activate the Cbl/

TC10 ubiquitin ligase pathway, which regulates traf-

ficking of insulin-responsive GLUT4 storage vesicles

to the plasma membrane[102]. These results indicate

that insulin signaling in T2D with obesity is not glob-

ally impaired; rather, the metabolic branch governing

glucose transport appears selectively affected. These

findings support the emerging concept of selective IR,

where discrete branches of metabolic signaling are

differentially impaired in T2D [41, 96, 103]. Further

studies with larger volunteer cohorts and detailed

temporal analyses of postprandial signaling dynam-

ics are needed to test this hypothesis and decipher

specific defects in insulin signaling that emerge in

obesity and prediabetes, ultimately shaping the mo-

lecular landscape of IR in overt T2D.

SECTION 7. HEPATIC LIPOTOXICITY

AND Β-CELL DYSFUNCTION:

WHEN THE LEVEE BREAKS

The early coexistence of dyslipidemia, insulin hy-

persecretion, and IR in prediabetes makes it difficult

to conclusively determine which of these features is

primary (Fig.  1). The molecular mechanism underly-

ing insulin secretion by β-cells and its dependence on

plasma glucose levels have been well characterized

[104]. Interestingly, in prediabetes, the arterial blood

levels of FFA and glucose (both fasting and postpran-

dial) typically remain within a normal range, while

insulin levels are almost persistently elevated in

obese individuals [74]. It is hard to imagine how and

why IR would arise in skeletal muscle under these

conditions, with compensatory hyperinsulinemia fol-

lowing. Consequently, some researchers believe that

hyperinsulinemia is the primary abnormality, rather

than the compensatory response, with IR developing

subsequently [10, 36, 37, 95]. Primary hyperinsulin-

emia could be caused by increased lipid influx into

β-cells, which stimulates insulin secretion [31], and/

or by elevated production of reactive oxygen species

in β-cells through mechanisms that are not yet fully

VOROTNIKOV et al.S386

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

understood  [9]. Regardless of the precise pathway,

these observations underscore the central role of dys-

lipidemia and/or excess dietary fat.

Blood enters the liver from the pancreas. The

liver and kidneys are the primary sites for insulin

clearance from the blood. Incomplete hepatic degra-

dation of insulin can therefore increase insulin levels

in systemic circulation and sustain hyperinsulinemia.

Normally, the liver removes up to 70% of insulin, but

in the presence of fat infiltration, it degrades only

30-40% of insulin [105]. When combined with insu-

lin hypersecretion by β-cells, this decreased hepatic

degradation likely contributes to basal hyperinsulin-

emia in response to surplus food and chronic excess

of lipids and carbohydrates in the venous outflow of

the portal vein system.

Adipose tissue, which takes up dietary fats in re-

sponse to insulin, protects the liver from fat infiltra-

tion. The levels of circulating FFA remain within the

normal range throughout the day, even in individuals

with moderate obesity [74,  75]. This suggests that in

prediabetes, adipose tissue effectively accommodates

increased dietary fat influx, thus protecting the liv-

er from fat infiltration. Between meals, when plas-

ma insulin is low, the liver adapts to the increased

FFA influx from adipose tissue by redirecting FFA

to lipoprotein TAG. The lack of such a protection in

conditions associated with overload of adipocyte fat

depots, such as lipodystrophy or morbid obesity, in-

creases the risks of ectopic fat accumulation and T2D

[74]. This again emphasizes the key role of adipose

tissue in T2D pathophysiology and in neutralizing po-

tential lipotoxicity of excess dietary fats.

Primary basal hyperinsulinemia may trigger a

cascade of events, such as fat accumulation in ad-

ipocytes due to insulin lipogenic activity [10,  11].

The prolonged duration of prediabetes may reflect

the slow progression of these events. Adipocyte hy-

pertrophy is associated with macrophage infiltration

and the development of latent inflammation  [8], re-

duction in the proliferative and regeneration poten-

tial of progenitor cells  [106], and emergence of IR in

adipose tissue  [7]. However, even in the absence of

adipose IR, hypertrophied adipocytes can serve as a

source of excessive postprandial FFA and leptin. De-

velopment of systemic leptin resistance may redirect

FFA to other tissues, causing ectopic obesity and IR

development in peripheral tissues [10,  32]. Determin-

ing whether, when, and to what extent IR develops in

adipose tissue appears critical for understanding the

pathophysiology of T2D.

The liver is the primary acceptor of FFA released

from adipose tissue, placing a substantial burden on

hepatic TAG synthetic machinery. Hepatocytes gen-

erate glycerol-3-phosphate for glyceroneogenesis, as

part of gluconeogenic pathway, using glycerol and,

potentially, lactate delivered from adipose tissue

[107]. In adipocytes, glucose conversion to lactate is

prioritized  [85], and the lactate cycle operates in adi-

pose tissue, similar to the Cori cycle in muscle  [108].

Normally, insulin suppresses adipose lipolysis and he-

patic gluconeogenesis, redirecting the FFA flux back

to the adipose tissue within minutes. IR in adipose

tissue is thought to remove the inhibition of lipolysis

in adipocytes, thus increasing FFA export and its de-

livery to hepatocytes, whereas hepatic IR unrepresses

glyceroneogenesis, promoting TAG synthesis and ac-

cumulation from incoming FFA  [4]. The combination

of adipose IR and hepatic IR disrupts coordinated

regulation of the opposing lipid fluxes, thus shifting

the balance toward TAG synthesis in the liver. The

export of TAG in lipoproteins facilitates redistribution

of the excessive fat to muscle and other tissues, thus

triggering ectopic obesity, potentially, even in the ab-

sence of leptin resistance. This again underscores the

metabolic connection between the liver and adipose

tissue and the role of adipose IR in the development

of hepatic IR.

According to this scenario, IR may develop last in

skeletal muscle and represent a protective adaptation,

reducing glucose influx into cells and lipogenesis in

response to increased availability of circulating FFA

[10]. Alternatively, IR may arise earlier, even first, in

skeletal muscle if it results from excessive dietary

fat. In this case, dietary lipids are transported from

intestinal enterocytes by chylomicrons in the lymph

into the vena cava and then into the arterial blood

via the pulmonary circuit. In this scenario, skeletal

muscle, like other organs, would be the first target

of FFA, further exacerbated by “spillover” effects as-

sociated with high LPL activity  [47]. The difference

between these scenarios appears to lie in the source

of plasma FFA: the chylomicron-derived FFA may first

promote IR in skeletal muscle, whereas the liver li-

poprotein-derived FFA may cause muscle IR at later

stages.

The skeletal muscle response to plasma FFA like-

ly also depends on the duration of FFA exposure [88,

89]. Whereas transient IR may develop through the

Randle glucose-fatty acid cycle  [22] during substantial

intervals between the meals, such as overnight fast-

ing, the risk of lipid-induced IR [4,  79] may increase

with a continuous and/or abundant influx of chylo-

microns into the circulation. Ectopic obesity is char-

acterized by gradual accumulation and slow shifts in

metabolic fluxes, the processes that may be accom-

panied by rewiring of intracellular insulin signaling

network  [42] and selective suppression of glucose

uptake  [41]. In contrast, the insulin signaling may be

switched off completely probably only under extreme

and/or long-term ectopic obesity  [30], as observed in

fat infusion and hyperinsulinemic clamp experiments

INSULIN RESISTANCE IN T2D PATHOPHYSIOLOGY S387

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

discussed in Sections  5 and  6. Regardless of the un-

derlying mechanism, skeletal muscle IR reduces glu-

cose clearance from the circulation, thereby causing

hyperglycemia and increasing glucose flux back to

the liver.

The clinical presentation of T2D suggests that fat-

ty liver and β-cell dysfunction are key indicators of

transition from prediabetes to T2D. Fatty liver likely

becomes clinically evident once circulating and adi-

pose fat depots are saturated with TAG. When hepatic

export of excess TAG via lipoproteins is exceeded, ke-

tone body production increases sharply and circulat-

ing FFA levels become elevated in people with severe

obesity  [68], as discussed in Section  4. It might be ex-

pected that under these conditions, the liver begins

to accumulate excess fat and develop ectopic obesi-

ty while suppressing insulin signaling and control

of glucose production. The resulting glucolipotoxicity

would damage β-cells, impair insulin secretion, and

lead to manifestation of overt T2D (Fig.  1). Thus, fatty

liver may be regarded as an early warning sign of

the metabolic levee break that culminates in systemic

fat spillover and glucolipotoxicity.

SECTION 8. CONCLUSIONS: THE FINAL CUT

The network organization of systemic metab-

olism and its regulation by insulin, complicated by

tissue-specific features, continues to hinder a full

comprehension of IR etiology and sequence of events

in T2D pathophysiology, which is essential for iden-

tifying effective therapeutic targets [4, 9, 12, 40, 42,

60, 95]. The framework outlined above integrates nu-

merous findings, of which only the most represen-

tative are cited, and therefore inevitably constitutes

a simplification. The progression from prediabetes

to T2D is shaped by multiple factors, their combi-

nations and interactions, resulting in substantial in-

dividual variability in disease histories and clinical

phenotypes. Elucidation of molecular and (patho)

physiological mechanisms that underlie this complex-

ity poses a major challenge for both basic research

and clinical medicine.

A central unresolved question is what triggers

the metabolic dysfunction? The above analysis points

to excessive nutrient availability and overnutrition,

the hallmarks of modern society, as major contribu-

tors. Primary hyperinsulinemia appears to represent

a critical early response; however, its underlying

causes and downstream consequences remain poor-

ly understood. Moreover, the tissue in which IR first

arises is still unknown. Whether skeletal muscle IR

constitutes an early initiating event or late adaptive

response to sustained hyperinsulinemia or lipid over-

load needs further investigation and careful scrutiny.

Hence, early diagnostics of IR and deep exploration

of its molecular mechanisms across multiple tissues

are highly important. In this respect, omics technolo-

gies are powerful tools for simultaneous monitoring

of hundreds of molecules and their post-translational

modifications [42, 99, 103], offering the possibility to

identify specific molecular perturbations at different

stages of prediabetes and in T2D.

Ectopic lipid accumulation and lipotoxicity ap-

pear to be central determinants in disease pathogen-

esis [30]; however, the underlying mechanisms re-

main incompletely understood and warrant further

investigation. Adipose tissue plays a pivotal role at

multiple steps of disease progression, yet molecular

drivers of adipose IR remain poorly defined. Remov-

al of adipose tissue to reduce fat mass, such as by

liposuction, are problematic due to potential impair-

ment of adipose endocrine function and/or regenera-

tive capacity. In contrast, modulation of adipogenesis

appears as a more promising method to upregulate

the lipid-oxidative capacity of adipocytes. Combining

these strategies with increased skeletal muscle activ-

ity to promote lipid utilization may offer the most

realistic prospects for preventing T2D. Finally, hepatic

steatosis becomes particularly critical during transi-

tion from prediabetes to overt T2D, potentially ne-

cessitating pharmacological interventions to prevent

irreversible metabolic deterioration.

Insulin therapy for prevention or early treatment

of T2D seems inappropriate [12] largely because IR

represents, in essence, an adaptive response to in-

creased availability of energy substrates. Exogenous

insulin would not eliminate the underlying causes of

IR and is likely to exacerbate metabolic stress by pro-

moting additional energy influx. Instead, glucose-low-

ering therapies and dietary interventions that reduce

fat mass are likely to be more effective. Achieving

rapid and sustained metabolic improvements will re-

quire the development of new therapeutics directed

at specific molecular targets. Identifying these targets

remains a priority in metabolic research.

Abbreviations

Akt protein kinase B/AKT1-3

BMI body mass index (kg/m

)

CoA coenzyme  A

Cbl/TC10 ubiquitin ligase Cbl/GTP-binding pro-

tein TC10

DAG diacylglycerol

ER endoplasmic reticulum

FFA free fatty acids

G6P glucose 6-phosphate

IR insulin resistance

LPL lipoprotein lipase

mTORC1

and mTORC2

mechanistic target of rapamycin

(mTOR) complexes  1  and  2

VOROTNIKOV et al.S388

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

IRS insulin receptor substrate

PKC

and nPKC

protein kinase  C and its novel

isoform

TAG triacylglycerol

T1D

and T2D

type  1  and  2 diabetes mellitus

VLDL very-low-density lipoprotein

Acknowledgments

The authors are grateful to N.  B.  Gusev, D.  V.  Popov,

and E.  I.  Yakupova for discussing the manuscript,

latest experimental results, and valuable comments.

We apologize to other authors whose work could not

be cited due to space limitations.

Contributions

A.V.V. and M.V.Sh. developed the concept and super-

vised the study; A.V.V., N .V. P., an d M.V.Sh. wrote and

discussed the manuscript; A.V.V. and M.V.Sh. edited the

manuscript.

Funding

This study was supported by the Russian Science

Foundation, grants no. 23-75-00027 (“Mechanisms of

adipocyte and vascular endothelial cell dysfunction

in metabolic disorders associated with obesity and

type 2 diabetes”) in part of Sections 2, 4, 5, 6, and 8)

and no. 22-15-00365-P (“Dynamics of hormonal-met-

abolic factors, markers of “metabolic memory” and

phenotypic features of mature and progenitor cells

of adipose tissue against the background of postbar-

iatric remission of type  2 diabetes mellitus”) in part

of Sections 1, 3, 4, and 7.

Ethics approval and consent to participate

This work does not contain any studies involving hu-

man or animal subjects.

Conflict of interest

The authors of this work declare that they have no

conflicts of interest.

REFERENCES

1. Ogurtsova, K., da Rocha Fernandes, J. D., Huang, Y., Linnenkamp, U., Guariguata, L., Cho, N. H., Cavan, D.,

Shaw, J. E., and Makaroff, L. E. (2017) IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for

2015 and 2040, Diab. Res. Clin. Pract., 128, 40-50, https://doi.org/10.1016/j.diabres.2017.03.024.

2. Dedov, I. I., Shestakova, M. V., Vikulova, O. K., Zheleznyakova, A. V., Isakov, M. A., Sazonova, D. V., and

Mokrysheva, N. G. (2023) Diabetes mellitus in the Russian Federation: dynamics of epidemiological indicators

according to the Federal Register of Diabetes Mellitus for the period 2010-2022, Diabetes Mellitus, 26, 104-123,

https://doi.org/10.14341/DM13035.

3. DeFronzo, R. A., and Tripathy, D. (2009) Skeletal muscle insulin resistance is the primary defect in type 2 dia-

betes, Diabetes Care, 32, S157-S163, https://doi.org/10.2337/dc09-S302.

4. Petersen, M. C., and Shulman, G. I. (2018) Mechanisms of insulin action and insulin resistance, Physiol. Rev.,

98, 2133-2223, https://doi.org/10.1152/physrev.00063.2017.

5. Reaven, G. M. (1988) Banting lecture 1988. Role of insulin resistance in human disease, Diabetes, 37, 1595-1607,

https://doi.org/10.2337/diabetes.37.12.1595.

6. Abel, E. D., Peroni, O., Kim, J. K., Kim, Y. B., Boss, O., Hadro, E., Minnemann, T., Shulman, G. I., and Kahn, B. B.

(2001) Adipose-selective targeting of the GLUT4 gene impairs insulin action in muscle and liver, Nature, 409,

729-733, https://doi.org/10.1038/35055575.

7. Stafeev, I. S., Vorotnikov, A. V., Ratner, E. I., Menshikov, M. Y., and Parfyonova, Y. V. (2017) Latent inflammation

and insulin resistance in adipose tissue, Int. J. Endocrinol., 2017, 5076732, https://doi.org/10.1155/2017/5076732.

8. Vorotnikov, A. V., Stafeev, I. S., Menshikov, M. Y., Shestakova, M. V., and Parfyonova, Y. V. (2019) Latent inflam-

mation and defect in adipocyte renewal as a mechanism of obesity-associated insulin resistance, Biochemistry

(Moscow), 84, 1329-1345, https://doi.org/10.1134/S0006297919110099.

9. Corkey, B. E., Deeney, J. T., and Merrins, M. J. (2021) What regulates basal insulin secretion and causes hyper-

insulinemia? Diabetes, 70, 2174-2182, https://doi.org/10.2337/dbi21-0009.

10. Unger, R. H. (2003) Lipid overload and overflow: metabolic trauma and the metabolic syndrome, Trends Endo-

crinol. Metab., 14, 398-403, https://doi.org/10.1016/j.tem.2003.09.008.

11. Pankov, Y. A. (2016) The adipogenic function and other biological effects of insulin, Biochemistry (Moscow)

Suppl. Series B, 10, 1-9, https://doi.org/10.1134/S199075081601011X.

12. Nolan, C. J., and Prentki, M. (2019) Insulin resistance and insulin hypersecretion in the metabolic syn-

drome and type 2 diabetes: Time for a conceptual framework shift, Diab. Vasc. Dis. Res., 16, 118-127, https://

doi.org/10.1177/1479164119827611.

13. Banting, F. G., and Best, C. H. (1922) The internal secretion of the pancreas, J. Lab. Clin. Med., VII, 251-266.

14. Himsworth, H. P. (1936) Diabetes mellitus: its differentiation into insulin-sensitive and insulin-insensitive types,

Lancet, 227, 127-130, https://doi.org/10.1016/S0140-6736(01)36134-2.

INSULIN RESISTANCE IN T2D PATHOPHYSIOLOGY S389

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

15. Yalow, R. S., and Berson, S. A. (1960) Immunoassay of endogenous plasma insulin in man, J. Clin. Invest., 39,

1157-1175, https://doi.org/10.1172/JCI104130.

16. Dole, V. P. (1956) A relation between non-esterified fatty acids in plasma and the metabolism of glucose, J. Clin.

Invest., 35, 150-154, https://doi.org/10.1172/JCI103259.

17. Reaven, G. M. (1995) The fourth Musketeer – from Alexandre Dumas to Claude Bernard, Diabetologia, 38, 3-13,

https://doi.org/10.1007/BF02369347.

18. Cahill, G. F., Leboeuf, B., and Renold, A. E. (1960) Factors concerned with the regulation of fatty acid metabolism

by adipose tissue, Am. J. Clin. Nutr., 8, 733-739, https://doi.org/10.1093/ajcn/8.5.733.

19. Vaughan, M. (1961) The metabolism of adipose tissue in vitro, J. Lipid Res., 2, 293-316, https://doi.org/10.1016/

S0022-2275(20)40471-7.

20. Cahill, G. F. (1961) Metabolic role of adipose tissue, Trans. Am. Clin. Climatol. Assoc., 73, 22-29.

21. Krycer, J. R., Yugi, K., Hirayama, A., Fazakerley, D. J., Quek, L. E., Scalzo, R., Ohno, S., Hodson, M. P., Ikeda, S.,

Shoji, F., Suzuki, K., Domanova, W., Parker, B. L., Nelson, M. E., Humphrey, S. J., Turner, N., Hoehn, K. L., Cooney,

G. J., Soga, T., Kuroda, S., and James, D. E. (2017) Dynamic metabolomics reveals that insulin primes the adi-

pocyte for glucose metabolism, Cell Rep., 21, 3536-3547, https://doi.org/10.1016/j.celrep.2017.11.085.

22. Randle, P. J., Garland, P. B., Hales, C. N., and Newsholme, E. A. (1963) The glucose fatty-acid cycle. Its role in

insulin sensitivity and the metabolic disturbances of diabetes mellitus, Lancet, 281, 785-789, https://doi.org/

10.1016/S0140-6736(63)91500-9.

23. Hue, L., and Taegtmeyer, H. (2009) The Randle cycle revisited: a new head for an old hat, Am. J. Physiol. En-

docrinol. Metab., 297, E578-E591, https://doi.org/10.1152/ajpendo.00093.2009.

24. Ashcroft, S. J. H., and Denton, R. M. (2021) Sir Philip John Randle, Biogr. Mem. Fellows R. Soc., 70, 359-385,

https://doi.org/10.1098/rsbm.2020.0044.

25. Randle, P. J., Kerbey, A. L., and Espinal, J. (1988) Mechanisms decreasing glucose oxidation in diabetes and

starvation: role of lipid fuels and hormones, Diabetes Metab. Res. Rev., 4, 623-638, https://doi.org/10.1002/

dmr.5610040702.

26. McGarry, J. D., Mannaerts, G. P., and Foster, D. W. (1977) A possible role for malonyl-CoA in the regulation of

hepatic fatty acid oxidation and ketogenesis, J. Clin. Invest., 60, 265-270, https://doi.org/10.1172/JCI108764.

27. McGarry, J. D. (2002) Banting lecture 2001: dysregulation of fatty acid metabolism in the etiology of type  2

diabetes, Diabetes, 51, 7-18, https://doi.org/10.2337/diabetes.51.1.7.

28. DeFronzo, R. A., Tobin, J. D., and Andres, R. (1979) Glucose clamp technique: a method for quantifying insulin

secretion and resistance, Am. J. Physiol., 237, E214-E223, https://doi.org/10.1152/ajpendo.1979.237.3.E214.

29. Shulman, G.I. (2000) Cellular mechanisms of insulin resistance, J. Clin. Invest., 106, 171-176, https://doi.org/10.1172/

JCI10583.

30. Shulman, G. I. (2014) Ectopic fat in insulin resistance, dyslipidemia, and cardiometabolic disease, N. Engl. J.

Med., 371, 2237-2238, https://doi.org/10.1056/NEJMc1412427.

31. Unger, R. H. (1995) Lipotoxicity in the pathogenesis of obesity-dependent NIDDM. Genetic and clinical implica-

tions, Diabetes, 44, 863-870, https://doi.org/10.2337/diabetes.44.8.863.

32. Unger, R. H., and Scherer, P. E. (2010) Gluttony, sloth and the metabolic syndrome: a roadmap to lipotoxicity,

Trends Endocrinol. Metab., 21, 345-352, https://doi.org/10.1016/j.tem.2010.01.009.

33. Summers, S. A., Chaurasia, B., and Holland, W. L. (2019) Metabolic Messengers: ceramides, Nat. Metab., 1,

1051-1058, https://doi.org/10.1038/s42255-019-0134-8.

34. Chavez, J. A., Knotts, T. A., Wang, L. P., Li, G., Dobrowsky, R. T., Florant, G. L., and Summers, S. A. (2003) A role

for ceramide, but not diacylglycerol, in the antagonism of insulin signal transduction by saturated fatty acids,

J. Biol. Chem., 278, 10297-10303, https://doi.org/10.1074/jbc.M212307200.

35. Chaurasia, B., and Summers, S. A. (2021) Ceramides in metabolism: Key lipotoxic players, Annu. Rev. Physiol.,

83, 303-330, https://doi.org/10.1146/annurev-physiol-031620-093815.

36. Corkey, B. E. (2012) Banting lecture 2011: Hyperinsulinemia: cause or consequence? Diabetes, 61, 4-13, https://

doi.org/10.2337/db11-1483.

37. Pories, W. J., and Dohm, G. L. (2012) Diabetes: have we got it all wrong? Hyperinsulinism as the culprit: surgery

provides the evidence, Diabetes Care, 35, 2438-2442, https://doi.org/10.2337/dc12-0684.

38. Lytrivi, M., Castell, A. L., Poitout, V., and Cnop, M. (2020) Recent insights into mechanisms of β-cell lipo- and

glucolipotoxicity in type 2 diabetes, J. Mol. Biol., 432, 1514-1534, https://doi.org/10.1016/j.jmb.2019.09.016.

39. Muoio, D. M. (2014) Metabolic inflexibility: when mitochondrial indecision leads to metabolic gridlock, Cell, 159,

1253-1262, https://doi.org/10.1016/j.cell.2014.11.034.

40. Goodpaster, B. H., and Sparks, L. M. (2017) Metabolic flexibility in health and disease, Cell Metab., 25, 1027-1036,

https://doi.org/10.1016/j.cmet.2017.04.015.

VOROTNIKOV et al.S390

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

41. James, D. E., Stöckli, J., and Birnbaum, M. J. (2021) The aetiology and molecular landscape of insulin resistance,

Nat. Rev. Mol. Cell Biol., 22, 751-771, https://doi.org/10.1038/s41580-021-00390-6.

42. Burchfield, J. G., Diaz-Vegas, A., and James, D. E. (2025) The insulin signalling network, Nat. Metab., 7, 1745-

1764, https://doi.org/10.1038/s42255-025-01349-z.

43. Diaz-Vegas, A., Sanchez-Aguilera, P., Krycer, J. R., Morales, P. E., Monsalves-Alvarez, M., Cifuentes, M., Rothermel,

B. A., and Lavandero, S. (2020) Is mitochondrial dysfunction a common root of noncommunicable chronic dis-

eases? Endocr. Rev., 41, bnaa005, https://doi.org/10.1210/endrev/bnaa005.

44. Diaz-Vegas, A., Madsen, S., Cooke, K. C., Carroll, L., Khor, J. X. Y., Turner, N., Lim, X. Y., Astore, M. A., Morris, J.,

Don, A., Garfield, A., Zarini, S., Zemski Berry, K. A., Ryan, A., Bergman, B. C., Brozinick, J. T., James, D. E.,

and Burchfield, J. G. (2023) Mitochondrial electron transport chain, ceramide and Coenzyme Q are linked in

a pathway that drives insulin resistance in skeletal muscle, Elife, 12, RP87340, https://doi.org/10.7554/eLife.

|87340.3.

45. DeFronzo, R. A. (2010) Insulin resistance, lipotoxicity, type 2 diabetes and atherosclerosis: the missing links. The

Claude Bernard Lecture 2009, Diabetologia, 53, 1270-1287, https://doi.org/10.1007/s00125-010-1684-1.

46. Van der Vusse, G. J. (2009) Albumin as fatty acid transporter, Drug Metab. Pharmacokinet., 24, 300-307, https://

doi.org/10.2133/dmpk.24.300.

47. Miles, J. M., and Nelson, R. H. (2007) Contribution of triglyceride-rich lipoproteins to plasma free fatty acids,

Horm. Metab. Res., 39, 726-729, https://doi.org/10.1055/s-2007-990273.

48. Curry, S. (2004) Plasma albumin as a fatty acid carrier, Adv. Mol. Cell Biol., 33, 29-46, https://doi.org/10.1016/

S1569-2558(03)33003-6.

49. Blache, D., Bourdon, E., Salloignon, P., Lucchi, G., Ducoroy, P., Petit, J. M., Verges, B., and Lagrost, L. (2015) Gly-

cated albumin with loss of fatty acid binding capacity contributes to enhanced arachidonate oxygenation and

platelet hyperactivity: relevance in patients with type 2 diabetes, Diabetes, 64, 960-972, https://doi.org/10.2337/

db14-0879.

50. Kravchenko, I. V., Furalyov, V. A., and Popov, V. O. (2020) Glycated albumin stimulates expression of inflamma-

tory cytokines in muscle cells, Cytokine, 128, 154991, https://doi.org/10.1016/j.cyto.2020.154991.

51. Freitas, P. A. C., Ehlert, L. R., and Camargo, J. L. (2017) Glycated albumin: a potential biomarker in diabetes,

Arch. Endocrinol. Metab., 61, 296-304, https://doi.org/10.1590/2359-3997000000272.

52. Spiller, S., Blüher, M., and Hoffmann, R. (2018) Plasma levels of free fatty acids correlate with type  2 diabetes

mellitus, Diabetes Obes. Metab., 20, 2661-2669, https://doi.org/10.1111/dom.13449.

53. Oliveira, A. F., Cunha, D. A., Ladriere, L., Igoillo-Esteve, M., Bugliani, M., Marchetti, P., and Cnop, M. (2015)

In vitro use of free fatty acids bound to albumin: A comparison of protocols, Biotechniques, 58, 228-233, https://

doi.org/10.2144/000114285.

54. Smathers, R. L., and Petersen, D.R. (2011) The human fatty acid-binding protein family: evolutionary divergences

and functions, Hum. Genomics, 5, 170-191, https://doi.org/10.1186/1479-7364-5-3-170.

55. Naquet, P., Kerr, E. W., Vickers, S. D., and Leonardi, R. (2020) Regulation of coenzyme A levels by degradation:

the ‘Ins and Outs’, Prog. Lipid Res., 78, 101028, https://doi.org/10.1016/j.plipres.2020.101028.

56. Zadoorian, A., Du, X., and Yang, H. (2023) Lipid droplet biogenesis and functions in health and disease, Nat.

Rev. Endocrinol., 19, 443-459, https://doi.org/10.1038/s41574-023-00845-0.

57. Li, X., Li, Z., Zhao, M., Nie, Y., Liu, P., Zhu, Y., and Zhang, X. (2019) Skeletal muscle lipid droplets and the ath-

lete’s paradox, Cells, 8, 249, https://doi.org/10.3390/cells8030249.

58. Warfel, J. D., Vandanmagsar, B., Dubuisson, O. S., Hodgeson, S. M., Elks, C. M., Ravussin, E., and Mynatt, R. L.

(2017) Examination of carnitine palmitoyltransferase 1 abundance in white adipose tissue: implications in

obesity research, Am. J. Physiol. Regul. Integr. Comp. Physiol., 312, R816-R820, https://doi.org/10.1152/ajpregu.

00520.2016.

59. Chouchani, E. T., Kazak, L., and Spiegelman, B. M. (2019) New advances in adaptive thermogenesis: UCP1 and

beyond, Cell Metab., 29, 27-37, https://doi.org/10.1016/j.cmet.2018.11.002.

60. DeFronzo, R. A. (2009) Banting Lecture. From the triumvirate to the ominous octet: a new paradigm for the

treatment of type 2 diabetes mellitus, Diabetes, 58, 773-795, https://doi.org/10.2337/db09-9028.

61. Rossetti, L., Giaccari, A., and DeFronzo, R. A. (1990) Glucose toxicity, Diabetes Care, 13, 610-630, https://

doi.org/10.2337/diacare.13.6.610.

62. Rossetti, L., Shulman, G. I., Zawalich, W., and DeFronzo, R. A. (1987) Effect of chronic hyperglycemia on in

vivo insulin secretion in partially pancreatectomized rats, J. Clin. Invest., 80, 1037-1044, https://doi.org/10.1172/

JCI113157.

63. Hotamışlıgil, G. S., and Bernlohr, D. A. (2015) Metabolic functions of FABPs – mechanisms and therapeutic im-

plications, Nat. Rev. Endocrinol., 11, 592-605, https://doi.org/10.1038/nrendo.2015.122.

INSULIN RESISTANCE IN T2D PATHOPHYSIOLOGY S391

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

64. Inouye, K. E., Prentice, K. J., Lee, A., Wang, Z. B., Dominguez-Gonzalez, C., Chen, M. X., Riveros, J. K., Burak,

M. F., Lee, G. Y., and Hotamışlıgil, G. S. (2023) Endothelial-derived FABP4 constitutes the majority of basal cir-

culating hormone and regulates lipolysis-driven insulin secretion, JCI Insight, 8, e164642, https://doi.org/10.1172/

jci.insight.164642.

65. Kolczyńska-Matysiak, K., Kassouf, T., Stegner, D., and Sumara, G. (2025) Platelets in the regulation of glucose

and lipid metabolism-functions beyond the maintenance of vascular integrity are being revealed, FEBS J., 292,

4992-5007, https://doi.org/10.1111/febs.70198.

66. Rabbani, N., and Thornalley, P. J. (2024) Hexokinase-linked glycolytic overload and unscheduled glycolysis in

hyperglycemia-induced pathogenesis of insulin resistance, beta-cell glucotoxicity, and diabetic vascular compli-

cations, Front. Endocrinol., 14, 1268308, https://doi.org/10.3389/fendo.2023.1268308.

67. Shah, M. S., and Brownlee, M. (2016) Molecular and cellular mechanisms of cardiovascular disorders in diabetes,

Circ. Res., 118, 1808-1829, https://doi.org/10.1161/CIRCRESAHA.116.306923.

68. Johansen, M., Afzal, S., Vedel-Krogh, S., Nielsen, S. F., Smith, G. D., and Nordestgaard, B. G. (2023) From plasma

triglycerides to triglyceride metabolism: effects on mortality in the Copenhagen General Population Study, Eur.

Heart J., 44, 4174-4182, https://doi.org/10.1093/eurheartj/ehad330.

69. Kahn, S. E., Hull, R. L., and Utzschneider, K. M. (2006) Mechanisms linking obesity to insulin resistance and

type 2 diabetes, Nature, 444, 840-846, https://doi.org/10.1038/nature05482.

70. Golay, A., Chen, Y. D., and Reaven, G. M. (1986) Effect of differences in glucose tolerance on insulin’s ability

to regulate carbohydrate and free fatty acid metabolism in obese individuals, J. Clin. Endocrinol. Metab., 62,

1081-1088, https://doi.org/10.1210/jcem-62-6-1081.

71. Fraze, E., Donner, C. C., Swislocki, A. L., Chiou, Y. A., Chen, Y. D., and Reaven, G. M. (1985) Ambient plasma

free fatty acid concentrations in noninsulin-dependent diabetes mellitus: evidence for insulin resistance, J. Clin.

Endocrinol. Metab., 61, 807-811, https://doi.org/10.1210/jcem-61-5-807.

72. Bierman, E. L., Dole, V. P., and Roberts, T. N. (1957) An abnormality of nonesterified fatty acid metabolism in

diabetes mellitus, Diabetes, 6, 475-479, https://doi.org/10.2337/diab.6.6.475.

73. Opie, L. H., and Walfish, P. G. (1963) Plasma free fatty acid concentrations in obesity, N. Engl. J. Med., 268,

757-760, https://doi.org/10.1056/NEJM196304042681404.

74. Frayn, K. N. (2019) Turning over our fat stores: the key to metabolic health. Blaxter Award Lecture 2018, Proc.

Nutr. Soc., 78, 398-406, https://doi.org/10.1017/S0029665118002598.

75. McQuaid, S. E., Hodson, L., Neville, M. J., Dennis, A. L., Cheeseman, J., Humphreys, S. M., Ruge, T., Gilbert, M.,

Fielding, B. A., Frayn, K. N., and Karpe, F. (2011) Downregulation of adipose tissue fatty acid trafficking in

obesity: a driver for ectopic fat deposition? Diabetes, 60, 47-55, https://doi.org/10.2337/db10-0867.

76. Karpe, F., Dickmann, J. R., and Frayn, K. N. (2011) Fatty acids, obesity, and insulin resistance: time for a re-

evaluation, Diabetes, 60, 2441-2449, https://doi.org/10.2337/db11-0425.

77. Charles, M. A., Eschwège, E., Thibult, N., Claude, J. R., Warnet, J. M., Rosselin, G. E., Girard, J., and Balkau, B.

(1997) The role of non-esterified fatty acids in the deterioration of glucose tolerance in Caucasian subjects:

results of the Paris Prospective Study, Diabetologia, 40, 1101-1106, https://doi.org/10.1007/s001250050793.

78. Arner, P., and Rydén, M. (2015) Fatty acids, obesity and insulin resistance, Obes. Facts, 8, 147-155, https://

doi.org/10.1159/000381224.

79. Samuel, V. T., Petersen, K. F., and Shulman, G. I. (2010) Lipid-induced insulin resistance: unravelling the mech-

anism, Lancet, 375, 2267-2277, https://doi.org/10.1016/S0140-6736(10)60408-4.

80. Rothman, D. L., Shulman, R. G., and Shulman, G. I. (1992) 31P nuclear magnetic resonance measurements of

muscle glucose-6-phosphate. Evidence for reduced insulin-dependent muscle glucose transport or phosphorylation

activity in non-insulin-dependent diabetes mellitus, J. Clin. Invest., 89, 1069-1075, https://doi.org/10.1172/JCI115686.

81. Shulman, G. I., Rothman, D. L., Jue, T., Stein, P., DeFronzo, R. A., and Shulman, R. G. (1990) Quantitation of

muscle glycogen synthesis in normal subjects and subjects with non-insulin-dependent diabetes by 13C nuclear

magnetic resonance spectroscopy, N. Engl. J. Med., 322, 223-228, https://doi.org/10.1056/NEJM199001253220403.

82. Trajanoski, Z., Brunner, G. A., Schaupp, L., Ellmerer, M., Wach, P., Pieber, T. R., Kotanko, P., and Skrabal, F.

(1997) Open-flow microperfusion of subcutaneous adipose tissue for on-line continuous ex vivo measurement

of glucose concentration, Diabetes Care, 20, 1114-1121, https://doi.org/10.2337/diacare.20.7.1114.

83. Cline, G. W., Jucker, B. M., Trajanoski, Z., Rennings, A. J., and Shulman, G. I. (1998) A novel 13C NMR method to

assess intracellular glucose concentration in muscle, in vivo, Am. J. Physiol., 274, E381-E389, https://doi.org/10.1152/

ajpendo.1998.274.2.E381.

84. Cline, G. W., Petersen, K. F., Krssak, M., Shen, J., Hundal, R. S., Trajanoski, Z., Inzucchi, S., Dresner, A., Rothman,

D. L., and Shulman, G. I. (1999) Impaired glucose transport as a cause of decreased insulin-stimulated muscle

glycogen synthesis in type 2 diabetes, N. Engl. J. Med., 341, 240-246, https://doi.org/10.1056/NEJM199907223410404.

VOROTNIKOV et al.S392

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

85. Krycer, J. R., Quek, L. E., Francis, D., Fazakerley, D. J., Elkington, S. D., Diaz-Vegas, A., Cooke, K. C., Weiss, F. C.,

Duan, X., Kurdyukov, S., Zhou, P. X., Tambar, U. K., Hirayama, A., Ikeda, S., Kamei, Y., Soga, T., Cooney, G. J.,

and James, D. E. (2020) Lactate production is a prioritized feature of adipocyte metabolism, J. Biol. Chem., 295,

83-98, https://doi.org/10.1074/jbc.RA119.011178.

86. Krycer, J. R., Quek, L. E., Francis, D., Zadoorian, A., Weiss, F. C., Cooke, K. C., Nelson, M. E., Diaz-Vegas, A.,

Humphrey, S. J., Scalzo, R., Hirayama, A., Ikeda,S., Shoji, F., Suzuki, K., Huynh, K., Giles, C., Varney, B., Nagarajan,

S. R., Hoy, A. J., Soga, T., Meikle, P. J., Cooney, G. J., Fazakerley, D. J., and James, D. E. (2020) Insulin signaling re-

quires glucose to promote lipid anabolism in adipocytes, J. Biol. Chem., 295, 13250-13266, https://doi.org/10.1074/

jbc.RA120.014907.

87. He, J., and Kelley, D. E. (2004) Muscle glycogen content in type 2 diabetes mellitus, Am. J. Physiol. Endocrinol.

Metab., 287, E1002-E1007, https://doi.org/10.1152/ajpendo.00015.2004.

88. Boden, G., Jadali, F., White, J., Liang, Y., Mozzoli, M., Chen, X., Coleman, E., and Smith, C. (1991) Effects of fat on

insulin-stimulated carbohydrate metabolism in normal men, J. Clin. Invest., 88, 960-966, https://doi.org/10.1172/

JCI115399.

89. Boden, G., Chen, X., Ruiz, J., White, J. V., and Rossetti, L. (1994) Mechanisms of fatty acid-induced inhibition of

glucose uptake, J. Clin. Invest., 93, 2438-2446, https://doi.org/10.1172/JCI117252.

90. Roden, M., Price, T. B., Perseghin, G., Petersen, K. F., Rothman, D. L., Cline, G. W., and Shulman, G. I. (1996)

Mechanism of free fatty acid-induced insulin resistance in humans, J. Clin. Invest., 97, 2859-2865, https://

doi.org/10.1172/JCI118742.

91. Dresner, A., Laurent, D., Marcucci, M., Griffin, M. E., Dufour, S., Cline, G. W., Slezak, L. A., Andersen, D. K.,

Hundal, R. S., Rothman, D. L., Petersen, K. F., and Shulman, G. I. (1999) Effects of free fatty acids on glu-

cose transport and IRS-1-associated phosphatidylinositol 3-kinase activity, J. Clin. Invest., 103, 253-259, https://

doi.org/10.1172/JCI5001.

92. Tkachuk, V. A., and Vorotnikov, A. V. (2014) Molecular mechanisms of insulin resistance development, Diabetes

Mellitus, 2014, 29-40, https://doi.org/10.14341/DM2014229-40.

93. Boura-Halfon, S., and Zick, Y. (2009) Phosphorylation of IRS proteins, insulin action, and insulin resistance, Am.

J. Physiol. Endocrinol. Metab., 296, E581-E591, https://doi.org/10.1152/ajpendo.90437.2008.

94. Samsonov, M. V., Podkuychenko, N. V., Khapchaev, A. Y., Efremov, E. E., Yanushevskaya, E. V., Vlasik, T. N.,

Lankin, V. Z., Stafeev, I. S., Skulachev, M. V., Shestakova, M. V., Vorotnikov, A. V., and Shirinsky, V. P. (2022)

AICAR protects vascular endothelial cells from oxidative injury induced by the long-term palmitate excess, Int.

J. Mol. Sci., 23, 211, https://doi.org/10.3390/ijms23010211.

95. Czech, M. P. (2017) Insulin action and resistance in obesity and type 2 diabetes, Nat. Med., 23, 804-814, https://

doi.org/10.1038/nm.4350.

96. Fazakerley, D. J., Krycer, J. R., Kearney, A. L., Hocking, S. L., and James, D. E. (2019) Muscle and adipose

tissue insulin resistance: malady without mechanism? J. Lipid Res., 60, 1720-1732, https://doi.org/10.1194/jlr.

R087510.

97. Sylow, L., Tokarz, V. L., Richter, E. A., and Klip, A. (2021) The many actions of insulin in skeletal muscle, the

paramount tissue determining glycemia, Cell Metab., 33, 758-780, https://doi.org/10.1016/j.cmet.2021.03.020.

98. Van Gerwen, J., Shun-Shion, A. S., and Fazakerley, D. J. (2024) Insulin signalling and GLUT4 trafficking in insulin

resistance, Biochem. Soc. Trans., 51, 1057-1069, https://doi.org/10.1042/BST20221066.

99. Yakupova, E. I., Podkuychenko, N. V., Smirnov, I. P., Zgoda, V. G., Vavilov, N. E., Lednev, E. M., Vepkhvadze, T. F.,

Tomilova, A. O., Shestakova, M. V., Vorotnikov, A. V., and Popov, D. V. (2025) Early phosphoproteomic response

of skeletal muscle to a meal in type 2 diabetes is comparable to that in healthy individuals, Biochemistry

(Moscow), Article submitted.

100. Makhnovskii, P. A., Lednev, E. M., Gavrilova, A. O., Kurochkina, N. S., Vepkhvadze, T. F., Shestakova, M. V., and

Popov, D. V. (2023) Dysregulation of early gene response to a mixed meal in skeletal muscle in obesity and

type 2 diabetes, Physiol. Genomics, 55, 468-477, https://doi.org/10.1152/physiolgenomics.00046.2023.

101. Lednev, E. M., Gavrilova, A. O., Vepkhvadze, T. F., Makhnovskii, P. A., Shestakova, M. V., and Popov, D. V.

(2023) Disturbances in dynamics of glucose, insulin, and C-peptide in blood after a normalized intake of

a mixed meal in obesity and type 2 diabetes mellitus, Hum. Physiol., 49, 668-674, https://doi.org/10.1134/

S0362119723600297.

102. Bogan, J. S. (2012) Regulation of glucose transporter translocation in health and diabetes, Annu. Rev. Biochem.,

81, 507-532, https://doi.org/10.1146/annurev-biochem-060109-094246.

103. Vorotnikov, A. V., Popov, D. V., and Makhnovskii, P. A. (2022) Signaling and gene expression in skeletal mus-

cles in type 2 diabetes: current results and OMICS perspectives, Biochemistry (Moscow), 87, 1021-1034, https://

doi.org/10.1134/S0006297922090139.

INSULIN RESISTANCE IN T2D PATHOPHYSIOLOGY S393

BIOCHEMISTRY (Moscow) Vol. 91 Suppl. 1 2026

104. Ashcroft, F. M. (2023) K

ATP

channels and the metabolic regulation of insulin secretion in health and disease:

the 2022 Banting medal for scientific achievement award lecture, Diabetes, 72, 693-702, https://doi.org/10.2337/

dbi22-0030.

105. Pivovarova, O., Bernigau, W., Bobbert, T., Isken, F., Möhlig, M., Spranger, J., Weickert, M. O., Osterhoff, M.,

Pfeiffer, A. F. H., and Rudovich, N. (2013) Hepatic insulin clearance is closely related to metabolic syndrome

components, Diabetes Care, 36, 3779-3785, https://doi.org/10.2337/dc12-1203.

106. Stafeev, I., Podkuychenko, N., Michurina, S., Sklyanik, I., Panevina, A., Shestakova, E., Yah’yaev, K., Fedenko, V.,

Ratner, E., Vorotnikov, A., Menshikov, M., Yashkov, Y., Parfyonova, Y., and Shestakova, M. (2019) Low prolifera-

tive potential of adipose-derived stromal cells associates with hypertrophy and inflammation in subcutaneous

and omental adipose tissue of patients with type 2 diabetes mellitus, J. Diabetes Compl., 33, 148-159, https://

doi.org/10.1016/j.jdiacomp.2018.10.011.

107. Beale, E. G., Hammer, R. E., Antoine, B., and Forest, C. (2002) Glyceroneogenesis comes of age, FASEB J., 16,

1695-1696, https://doi.org/10.1096/fj.02-0407rev.

108. Brooks, G. A. (2018) The science and translation of lactate shuttle theory, Cell Metab., 27, 757-785, https://

doi.org/10.1016/j.cmet.2018.03.008.

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