Genetics and Clinical Characteristics of PPARγ Variant-Induced Diabetes in a Chinese Han Population

The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion

BACKGROUND

Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field.

METHODS

Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice.

RESULTS

There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted.

CONCLUSIONS

We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

Identification and Characteristics of Novel Mutations in Nonsyndromic Monogenic Obesity

Nonsyndromic monogenic obesity (NSMO) is a class of individual obesity that is independent of the environment and caused by a single gene mutation. It is mostly caused by mutations in LEP, LEPR, PCSK1, as well as some rare mutations in UCP3, NR0B2, and PPARG. Among 30 obesity patients, five patients are identified with positive gene detection. For the first time, the c.624C>T mutation associated with PCSK1, and the c.50G>A and c.293_301delinsAC mutations associated with NR0B2, as well as the obesity phenotype mutation (c.284A>G) associated with PPARG is confirmed. Following this, the genotype-clinical phenotype, mutation hotspots, and mutation distributions of each gene are summarized, and the genetic characteristics of NSMO are analyzed. The locations of mutation c.50G>A, and c.284A>G are highly conserved according to the sequencing alignment. According to the findings, the c.624C>T mutation in PCSK1 is a newly discovered synonymous mutation, but it can result in significant early-onset obesity. Additionally, the mutation of c.284A>G(PPARG) can lead to a variety of clinical phenotypes and the mutation of UCP3 and NR0B2 may increase the risk of type 2 diabetes mellitus. This study enriches the human NSMO gene mutation database and provides a scientific basis for clinically accurate diagnosis and treatment.

PPARγ Gene Polymorphisms, Metabolic Disorders, and Coronary Artery Disease

Being activated by endogenous and exogenous ligands, nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ) enhances insulin sensitivity, promotes adipocyte differentiation, stimulates adipogenesis, and has the properties of anti-atherosclerosis, anti-inflammation, and anti-oxidation. The Human PPARγ gene (PPARG) contains thousands of polymorphic loci, among them two polymorphisms (rs10865710 and rs7649970) in the promoter region and two polymorphisms (rs1801282 and rs3856806) in the exonic region were widely reported to be significantly associated with coronary artery disease (CAD). Mechanistically, PPARG polymorphisms lead to abnormal expression of PPARG gene and/or dysfunction of PPARγ protein, causing metabolic disorders such as hypercholesterolemia and hypertriglyceridemia, and thereby increasing susceptibility to CAD.