Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes.

AIMS/HYPOTHESIS: We sought to subtype South East Asian patients with type 2 diabetes by de novo cluster analysis on clinical variables, and to determine whether the novel subgroups carry distinct genetic and lipidomic features as well as differential cardio-renal risks. METHODS: Analysis by k-means algorithm was performed in 687 participants with recent-onset diabetes in Singapore. Genetic risk for beta cell dysfunction was assessed by polygenic risk score. We used a discovery-validation approach for the lipidomics study. Risks for cardio-renal complications were studied by survival analysis. RESULTS: Cluster analysis identified three novel diabetic subgroups, i.e. mild obesity-related diabetes (MOD, 45%), mild age-related diabetes with insulin insufficiency (MARD-II, 36%) and severe insulin-resistant diabetes with relative insulin insufficiency (SIRD-RII, 19%). Compared with the MOD subgroup, MARD-II had a higher polygenic risk score for beta cell dysfunction. The SIRD-RII subgroup had higher levels of sphingolipids (ceramides and sphingomyelins) and glycerophospholipids (phosphatidylethanolamine and phosphatidylcholine), whereas the MARD-II subgroup had lower levels of sphingolipids and glycerophospholipids but higher levels of lysophosphatidylcholines. Over a median of 7.3 years follow-up, the SIRD-RII subgroup had the highest risks for incident heart failure and progressive kidney disease, while the MARD-II subgroup had moderately elevated risk for kidney disease progression. CONCLUSIONS/INTERPRETATION: Cluster analysis on clinical variables identified novel subgroups with distinct genetic, lipidomic signatures and varying cardio-renal risks in South East Asian participants with type 2 diabetes. Our study suggests that this easily actionable approach may be adapted in other ethnic populations to stratify the heterogeneous type 2 diabetes population for precision medicine.

Risk of Incident Heart Failure in Individuals With Early-Onset Type 2 Diabetes.

CONTEXT: Early-onset diabetes has been associated with unfavorable cardiovascular risk but data on heart failure (HF) in this subpopulation are scarce. OBJECTIVE: We aimed to study the risk of, and risk factors for, incident HF in individuals with early-onset type 2 diabetes. METHODS: We studied 606 individuals with type 2 diabetes diagnosed before 40 years of age (early-onset) and 1258 counterparts with diabetes diagnosed from 41 to 65 years of age (usual-onset) with no HF history, at a regional hospital, over a median follow-up period of 7.1 years. Incident HF by European Cardiology Society criteria was determined. RESULTS: A total of 62 and 108 HF events were identified in the early- and usual-onset groups (1.55 and 1.29 per 100 patient-years), respectively. Compared with usual-onset counterparts, individuals with early-onset diabetes had a 1.20-fold unadjusted (95% CI, 0.88-1.63; P = 0.26) and 1.91-fold age-adjusted (95% CI, 1.37-2.66; P < 0.001) hazard ratio (HR) for incident HF. Adjustment for traditional cardiometabolic risk factors only moderately mitigated the hazards (adjusted HR 1.69; 95% CI, 1.19-2.40; P = 0.003). However, additional adjustment for estimated glomerular filtration rate and albuminuria markedly attenuated the association of early-onset age with incident HF (adjusted HR 1.24; 95% CI, 0.87-1.77; P = 0.24). Notably, a long diabetes duration was not significantly associated with HF risk after accounting for kidney measures. CONCLUSION: Individuals with early-onset diabetes have at least the same absolute risk and a 2-fold age-adjusted relative risk for incident HF. Excess cardiorenal risk factors but not a long diabetes duration are main drivers for HF development in this diabetic population.

Association of Plasma Leucine-Rich α-2 Glycoprotein 1, a Modulator of Transforming Growth Factor-ß Signaling Pathway, With Incident Heart Failure in Individuals With Type 2 Diabetes.

OBJECTIVE: Leucine-rich α-2 glycoprotein 1 (LRG1) is a circulating protein potentially involved in several pathways related to pathogenesis of heart failure (HF). We aimed to study whether plasma LRG1 is associated with risks of incident HF and hospitalization attributable to HF (HHF) in individuals with type 2 diabetes. RESEARCH DESIGN AND METHODS: A total of 1,978 individuals with type 2 diabetes were followed for a median of 7.1 years (interquartile range 6.1-7.6). Association of LRG1 with HF was studied using cause-specific Cox regression models. RESULTS: In follow-up, 191 incident HF and 119 HHF events were identified. As compared with quartile 1, participants with LRG1 in quartiles 3 and 4 had 3.60-fold (95% CI 1.63-7.99) and 5.99-fold (95% CI 2.21-16.20) increased risk of incident HF and 5.88-fold (95% CI 1.83-18.85) and 10.44-fold (95% CI 2.37-45.98) increased risk of HHF, respectively, after adjustment for multiple known cardiorenal risk factors. As a continuous variable, 1 SD increment in natural log-transformed LRG1 was associated with 1.78-fold (95% CI 1.33-2.38) adjusted risk of incident HF and 1.92-fold (95% CI 1.27-2.92) adjusted risk of HHF. Adding LRG1 to the clinical variable-based model improved risk discrimination for incident HF (area under the curve [AUC] 0.79-0.81; P = 0.02) and HHF (AUC 0.81-0.84; P = 0.02). CONCLUSIONS: Plasma LRG1 is associated with risks of incident HF and HHF, suggesting that it may potentially be involved in pathogenesis of HF in individuals with type 2 diabetes. Additional studies are warranted to determine whether LRG1 is a novel biomarker for HF risk stratification.

Spectrum of mutations in index patients with familial hypercholesterolemia in Singapore: Single center study.

BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is an autosomal dominant genetic disease characterized by the presence of high plasma low density lipoproteins cholesterol (LDL-c). Patients with FH, with mutation detected, are at increased risk of premature cardiovascular disease compared to those without mutations. The aim of the study was to assess the type of mutations in patients, clinically diagnosed with FH in Singapore. METHODS: Patients (probands) with untreated/highest on-treatment LDL-c>4.9 mmol/l were recruited (June 2015 to April 2017). Anthropometric, biochemical indices, blood and family history were collected. DNA was extracted and Next Generation Sequencing (NGS) was performed in 26 lipid-related genes, including LDLR, APOB and PCSK9, and validated using Sanger. Multiplex-ligation probe analyses for LDLR were performed to identify large mutation derangements. Based on HGVS nomenclature, LDLR mutations were classified as "Null"(nonsense, frameshift, large rearrangements) and "Defective"(point mutations which are pathogenic). RESULTS: Ninety-six probands were recruited: mean age: (33.5 ±â€¯13.6) years. 52.1% (n = 50) of patients had LDLR mutations, with 15 novel mutations, and 4.2% (n = 4) had APOB mutations. Total cholesterol (TC) and LDL-c were significantly higher in those with LDLR mutations compared to APOB and no mutations [(8.53 ±â€¯1.52) vs. (6.93 ±â€¯0.47) vs. (7.80 ±â€¯1.32)] mmol/l, p = 0.012 and [(6.74 ±â€¯0.35) vs. (5.29 ±â€¯0.76) vs. (5.98 ±â€¯1.23)] mmol/l, p=0.005, respectively. Patients with "null LDLR" mutations (n = 13) had higher TC and LDL-c than "defective LDLR" mutations (n = 35): [(9.21 ±â€¯1.60) vs. (8.33 ±â€¯1.41)]mmol/l, p = 0.034 and [(7.43 ±â€¯1.47) vs. (6.53 ±â€¯1.21)]mmol/l, p=0.017, respectively. CONCLUSIONS: To our knowledge, this is the first report of mutation detection in patients with clinically suspected FH by NGS in Singapore. While percentage of mutations is similar to other countries, the spectrum locally differs.