About

Amit Majithia is an Associate Professor of Medicine at UCSD, with a research focus on cardiovascular disease genetics, insulin resistance, and metabolic disorders. His work involves credentialing novel cardiovascular disease genes through sex-specific genomic investigations and combining experiments of humans and nature to target human insulin resistance. He has contributed to understanding the genetic and metabolic underpinnings of diabetes, obesity, and related metabolic conditions, utilizing high-throughput experiments, genomic analysis, and clinical trials. His research aims to elucidate mechanisms of glucose regulation, lipid metabolism, and vascular complications, with a particular interest in translating genomic discoveries into therapeutic targets and clinical interventions.

Research topics

• Biology
• Genetics
• Medicine
• Endocrinology
• Computational biology
• Cartography
• Physical therapy
• Bioinformatics
• Nursing

Selected publications

• Disentangling the Effects of Chromosomal Versus Hormonal Sex on Insulin Resistance

  Metabolism · 2026-03-05

  articleSenior author
  PublisherDOI

• G2PT: a genotype-phenotype transformer to assess and explain polygenic risk

  Open MIND · 2026-04-23

  otherOpen access

  G2PT: A Genotype-to-Phenotype Transformer This release corresponds to the version of G2PT described in: Lee, Ingoo et al. "G2PT: a genotype-phenotype transformer to assess and explain polygenic risk." Genome Biology (2026). About G2PT is a hierarchical graph transformer framework for modeling information flow among genetic variants, genes, multigenic systems, and phenotypes. This release includes code for: Model training and evaluation on UK Biobank metabolic traits (TG/HDL, LDL, T2D) Benchmarking against PRS and machine learning baselines Transformer attention-based interpretation of genes and biological systems Epistatic interaction detection Requirements See README.md for installation and usage instructions. License This project is licensed under the MIT License.

  PublisherDOI

• G2PT: a genotype-phenotype transformer to assess and explain polygenic risk

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-23

  otherOpen access

  G2PT: A Genotype-to-Phenotype Transformer This release corresponds to the version of G2PT described in: Lee, Ingoo et al. "G2PT: a genotype-phenotype transformer to assess and explain polygenic risk." Genome Biology (2026). About G2PT is a hierarchical graph transformer framework for modeling information flow among genetic variants, genes, multigenic systems, and phenotypes. This release includes code for: Model training and evaluation on UK Biobank metabolic traits (TG/HDL, LDL, T2D) Benchmarking against PRS and machine learning baselines Transformer attention-based interpretation of genes and biological systems Epistatic interaction detection Requirements See README.md for installation and usage instructions. License This project is licensed under the MIT License.

  PublisherDOI

• Author Reply to Peer Reviews of A genotype-phenotype transformer to assess and explain polygenic risk

  2026-01-16

  peer-review
  PublisherDOI

• An ancestry-enriched HNF4A variant and GP2 reveal distinct mechanisms of type 2 diabetes in exome-wide study of 13,674 cases and 41,024 controls

  medRxiv · 2025-09-26

  preprintOpen access

  Abstract / Introductory Paragraph Type 2 diabetes (T2D) is a common and complex metabolic condition with significant heterogeneity within and across ancestries 1–4 . Compared with individuals of European ancestry (EUR), people of south Asian ancestry (SAS) have two to four-fold higher risk of T2D, develop the disease at younger ages and lower body mass index (BMI), and experience more rapid progression to complications 5–10 . Understanding the genetic basis of this is hindered by low representation of south Asians in genetic studies. Here, we perform an exome-wide association study of T2D in 13,674 cases and 41,024 controls from the Genes & Health study of British Pakistani and Bangladeshi individuals. We identify a novel rare variant in HNF4A – a canonical monogenic diabetes / MODY gene, in which missense variants would be expected to increase T2D risk. Surprisingly, HNF4A Pro437Ser is associated with a halved risk of T2D and reduced risk of diabetes-related complications but increased non-HDL cholesterol. We additionally characterise a T2D risk-increasing variant which is common only in South and East Asian ancestral groups ( GP2 Val429Met), which is associated with lower BMI and phenotypic and genetic markers of insulin deficiency. We validate our findings through replication in independent multi-ancestry cohorts, in vitro functional assays, and integration of proteogenomic analysis. These findings highlight how the study of under-represented populations can identify biological mechanisms associated with disease phenotypes enriched in those populations.

  PublisherOA PDFDOI

• Accuracy of Factory-Calibrated Continuous Glucose Monitors in Critically Ill Patients Receiving Intravenous Insulin: A Prospective Clinical Trial of Two Leading Systems

  Journal of Diabetes Science and Technology · 2025-05-08 · 1 citations

  articleOpen access

  BACKGROUND: Continuous glucose monitors (CGMs) are increasingly being used to guide glucose management in the hospital. However, uncertainty regarding their accuracy in this setting remains. METHODS: We conducted a nonrandomized, open-label, clinically blinded prospective trial of the Dexcom G6 Pro (G6P) and FreeStyle Libre Pro (FLP) in the inpatient setting among critically ill hospitalized patients (n = 40) requiring continuous intravenous insulin infusion. In parallel with CGM data, reference serum (Lab) glucose and point-of-care (POC) glucose values were obtained. On completion of the study, CGM and reference values were analyzed to assess CGM accuracy. RESULTS: A total of 1015 matched G6P-Lab pairs had a mean absolute relative difference (MARD) of 22.7%, 2369 G6P-POC pairs had an MARD of 22.9%, 1006 matched FLP-Lab pairs had an MARD of 25.2%, and 2353 FLP-POC pairs had an MARD of 27.0%. Both CGM systems demonstrated considerable inter-patient variability in sensor accuracy and tended to underestimate glucose in comparison with the reference values. Rarely were low reference values overestimated by either sensor. CONCLUSIONS: Factory-calibrated continuous glucose monitors may require accuracy validation and per-patient calibration for inpatient use in critically ill patients.

  PublisherDOI

• Longitudinal Metabolic Trajectories in Diabetes Prevention Program Participants Reveal Subgroups With Varying Micro- and Macrovascular Complication Risks

  Diabetes Care · 2025-08-26 · 5 citations

  articleOpen access

  OBJECTIVE: Type 2 diabetes (T2D) and its associated complications develop heterogeneously over decades, but few studies span the progression from prediabetes to clinical events. We investigated whether long-term metabolic trajectories beginning in prediabetes delineate subgroups with differential complication risk. RESEARCH DESIGN AND METHODS: Clinical data from 1,732 Diabetes Prevention Program/Outcomes Study participants (follow-up 19 years) were analyzed across 12 phenotypes. Tensor decomposition was used to capture longitudinal patterns, and Gaussian mixture modeling was used to define longitudinal clusters. Cluster-specific complications were quantified with Cox and logistic regression. RESULTS: Four clusters emerged. Clusters 1 and 2 (73% of participants) maintained stable glycemia, blood pressure, and lipids. Although 49% and 71%, respectively, developed T2D, cumulative micro- and macrovascular events remained low. Cluster 3 (12%) showed the steepest rise in insulin resistance and hyperglycemia, with 92% of the subgroup progressing to T2D and a markedly higher rate of retinopathy (odds ratio [OR] 8.8, 95% CI 3.9-20.1) and neuropathy (OR 3.4, 95% CI 2.1-5.5). Cluster 4 (15%) presented with baseline microalbuminuria often prior to the development of T2D (73%). It was distinguished by progressive estimated glomerular filtration rate decline and a doubling of cardiovascular events (hazard ratio 2.0, 95% CI 1.4-3.0), despite serum lipids comparable with other groups. CONCLUSIONS: Two-thirds of individuals with prediabetes follow metabolically resilient trajectories, whereas distinct insulin-resistant or renal-dysfunction trajectories precede micro- or macrovascular complications, respectively. The optimal window for macrovascular complication prevention in individuals with prediabetes microalbuminuria may precede progression to T2D.

  PublisherOA PDFDOI

• Longitudinal metabolic trajectories in Diabetes Prevention Program participants reveal subgroups with varying micro and macrovascular complication risks

  2025-08-26

  preprintOpen accessSenior author

  <p dir="ltr"><b>Objective</b>: Type 2 diabetes (T2D) and its associated complications develop heterogeneously over decades, but few studies span the progression from prediabetes to clinical events. We investigated whether long-term metabolic trajectories beginning in prediabetes delineate subgroups with differential complication risk.</p><p><br></p><p dir="ltr"><b>Research Design and Methods</b>: Clinical data from 1,732 Diabetes Prevention Program/Outcomes Study participants (follow-up 19 years) were analyzed across 12 phenotypes. Tensor decomposition was used to capture longitudinal patterns, and Gaussian Mixture Modeling to define longitudinal clusters. Cluster-specific complications were quantified with Cox and logistic regression.</p><p><br></p><p dir="ltr"><b>Results</b>: Four clusters emerged. Clusters 1 and 2 (73% of participants) maintained stable glycemia, blood pressure, and lipids. Although 49% and 71% developed T2D, cumulative micro and macrovascular events remained low. Cluster 3 (12%) showed the steepest rise in insulin resistance and hyperglycemia, with 92% of participants progressing to T2D and markedly higher rate of retinopathy (odds ratio (OR) 8.8, 95% CI 3.9-20.1) and neuropathy (OR 3.4, 95% CI 2.1-5.5). Cluster 4 (15%) presented with baseline microalbuminuria often prior to the development of T2D (73%). It was distinguished by progressive eGFR decline and a doubling of cardiovascular events (hazard ratio 2.0, 95% CI 1.4-3.0) despite comparable serum lipids to other groups.</p><p><br></p><p dir="ltr"><b>Conclusions</b>: Two-thirds of individuals with prediabetes follow metabolically resilient trajectories, whereas distinct insulin-resistant or renal-dysfunction trajectories precede micro or macrovascular complications respectively. The optimal window for macrovascular complication prevention in individuals with prediabetic microalbuminuria may precede progression to T2D.</p>

  PublisherDOI

• Adipocyte heparan sulfate determines type 2 diabetes susceptibility in mice via FGF1-Mediated glucose regulation

  Molecular Metabolism · 2025-10-09

  articleOpen access

  Obesity is the principal driver of insulin resistance, and lipodystrophy is also linked with insulin resistance, emphasizing the vital role of adipose tissue in glucose homeostasis. The quality of adipose tissue expansion is a critical determinant of insulin resistance predisposition, with individuals suffering from metabolic unhealthy adipose expansion exhibiting greater risk. Adipocytes are pivotal in orchestrating metabolic adjustments in response to nutrient intake and cell intrinsic factors that positively regulate these adjustments are key to prevent Type-2 diabetes. Employing unique genetic mouse models, we established the critical involvement of heparan sulfate (HS), a fundamental element of the adipocyte glycocalyx, in upholding glucose homeostasis during dietary stress. Genetic models that compromise adipocyte HS accelerate the development of high-fat diet-induced hyperglycemia and insulin resistance, independent of weight gain. Mechanistically, we show that perturbations in adipocyte HS disrupts endogenous FGF1 signaling, a key nutrient-sensitive effector. Furthermore, compromising adipocyte HS composition detrimentally impacts FGF1-FGFR1-mediated endocrinization, with no significant improvement observed in glucose homeostasis. Our data establish adipocyte HS composition as a determinant of Type 2 diabetes susceptibility and the critical dependency of the endogenous adipocyte FGF1 metabolic pathway on HS. • Adipocyte heparan sulfate does not impact diet-induced weight gain. • Adipocyte heparan sulfate sulfation compromises glucose regulation and insulin sensitivity under nutrient stress. • Mice with reduced HS sulfation show increased insulin resistance and fatty liver disease in a diet-induced obesity model. • Mechanistically HS sulfation is essential for the glucose-lowering effect of FGF1, a critical paracrine insulin sensitizer in adipose tissue.

  PublisherDOI

• <b>An alternatively translated isoform of </b><b><i>PPARG</i></b><b> proposes AF-1 domain inhibition as an insulin sensitization target</b>

  2025-01-24

  preprintOpen accessSenior author

  <p dir="ltr">PPARγ is the pharmacological target of thiazolidinediones (TZDs), potent insulin sensitizers that prevent metabolic disease morbidity but are accompanied by side effects such as weight gain, in part due to non-physiological transcriptional agonism. Using high throughput genome engineering, we targeted nonsense mutations to every exon of <i>PPARG</i>, finding an ATG in Exon 2 (chr3:12381414, CCDS2609 c.A403) that functions as an alternative translational start site. This downstream translation initiation site gives rise to a PPARγ protein isoform (M135), preferentially generated from alleles containing nonsense mutations upstream of c.A403. PPARγ M135 retains the DNA and ligand binding domains of full-length PPARγ but lacks the N-terminal AF-1 domain. Despite being truncated, PPARγ M135 shows increased transactivation of target genes, but only in the presence of agonists. Accordingly, human missense mutations disrupting AF-1 domain function actually increase agonist-induced cellular PPARγ activity compared to wild-type (WT), and carriers of these AF-1 disrupting variants are protected from metabolic syndrome. Thus, we propose the existence of PPARγ M135 as a fully functional, alternatively translated isoform that may be therapeutically generated to treat insulin resistance-related disorders.</p>

  PublisherDOI

Recent grants

• Prospective Functional Characterization of All Possible Missense Variants in HNF1A

  NIH · $164k · 2017–2020

• Combining experiments of man and nature to target human insulin resistance

  NIH · $2.9M · 2026–2030

• Making sense of sequence - high throughput experiments in human adipocytes

  NIH · $768k · 2014–2020

Frequent coauthors

• David Altshuler

  51 shared

• José C. Florez

  Harvard University

  28 shared

• Krishna Chatterjee

  University of Cambridge

  21 shared

• Maura Agostini

  21 shared

• Stephen O’Rahilly

  University of Cambridge

  21 shared

• David B. Savage

  Wellcome/MRC Institute of Metabolic Science

  21 shared

• Alan R. Kimmel

  National Institutes of Health

  20 shared

• Sekar Kathiresan

  Massachusetts General Hospital

  19 shared