Biomedical subjects

Kaifeng Lu

Publications and source records attributed to Kaifeng Lu.

3 recordsLinked to original sources

PubMed2026

Genome-wide association study of sarcopenia index reveals sex-stratified genetic architecture.

BACKGROUND: The sarcopenia index (SI), defined as the ratio of serum creatinine to cystatin C, is a proposed biomarker of muscle mass and sarcopenia, yet its genomic basis and genetic architecture remain largely unexplored. METHODS: We performed combined-sex and sex-stratified genome-wide association studies of SI in the UK Biobank. We examined the overlap between SI-associated loci and loci previously reported for sarcopenia-related traits. We assessed sexually dimorphic effects and gene-sex interactions, performed fine-mapping, and conducted credible gene prioritization, motif and transcription factor binding enrichment, gene-set enrichment, linkage disequilibrium score regression, and cross-phenotype colocalization. RESULTS: We identified 774 unique independent SI-associated loci across all analyses, with 747 detected in the combined-sex GWAS, 283 in the male-stratified GWAS, and 311 in the female-stratified GWAS; 367 of these loci had not been previously reported for conventional sarcopenia-related traits. Sex-stratified analyses highlighted the rs1145093-chr15q21.1-GATM region, where CARMA identified sex-differentiated causal variants. We prioritized 17 male-biased and 11 female-biased credible genes. Enrichment analyses implicated androgen receptor and GATA4 in males, and ESR1 and MYOD1 in females. Enrichment revealed shared pathways involving inflammation, cellular stress, and aging-related processes. LDSC showed inverse genetic correlations between SI and heart failure (rg = -0.19, p = 2.30 × 10- 9) and metabolic syndrome (rg = -0.12, p = 8.49 × 10- 8), and a positive correlation with chronic kidney disease. Compared with female SI, male SI exhibited two additional loci showing colocalization with four metabolic traits. CONCLUSIONS: These findings clarify the genetic architecture of SI and reveal sex-dependent mechanisms underlying sarcopenia, supporting precision risk assessment and targeted interventions.

Humans↗

PubMed2006

Efficacy and safety of the dipeptidyl peptidase-4 inhibitor sitagliptin added to ongoing pioglitazone therapy in patients with type 2 diabetes: a 24-week, multicenter, randomized, double-blind, placebo-controlled, parallel-group study.

OBJECTIVE: The efficacy and tolerability of the dipeptidyl peptidase-4 inhibitor sitagliptin added to ongoing pioglitazone therapy were assessed in patients with type 2 diabetes and inadequate glycemic control (glycosylated hemoglobin [HbA(1c)] > or =7% and < or =10%) while receiving a stable dose of pioglitazone. METHODS: This was a 24-week, multicenter, randomized, double-blind, placebo-controlled, parallel group study in patients aged > or =18 years (ClinicalTrials. gov NCT00086502). At screening, all patients began a diet/exercise program that continued throughout the study period. Patients taking antihyperglycemic therapy other than pioglitazone underwent a washout of this therapy and entered an 8- to 14-week open-label pioglitazone dose-titration/stabilization period. Patients with an HbA(1c) > or =7% and < or =10% at the end of this period entered a 2-week, single-blind, placebo run-in period (total duration of run-in period, up to 21 weeks). Patients who had been receiving pioglitazone monotherapy (30 or 45 mg/d) and had an HbA(1c) > or =7% and < or =10% entered the 2-week, single-blind, placebo run-in period directly. Thus, at the time of randomization, all patients were receiving ongoing pioglitazone (30 or 45 mg/d). Patients were randomized in a 1:1 ratio to receive sitagliptin 100 mg once daily or placebo for 24 weeks. The primary efficacy end point was the change from baseline in HbA(1c) at week 24. Secondary efficacy end points included the change from baseline in fasting plasma glucose (FPG), insulin, and proinsulin; the Homeostasis Model Assessment beta-cell function and insulin-resistance indexes; the proinsulin/ insulin ratio; the Quantitative Insulin Sensitivity Check Index; the percent changes from baseline in selected lipid parameters; the proportion of patients meeting the American Diabetes Association HbA(1c), goal of <7.0%; the proportion of patients requiring metformin rescue therapy; and the time to the initiation of rescue therapy. RESULTS: One hundred seventy-five patients were randomized to receive sitagliptin, and 178 were randomized to receive placebo. The mean (SD) baseline HbAlc value was 8.1% (0.8) in the sitagliptin group and 8.0% (0.8) in the placebo group. After 24 weeks, sitagliptin added to pioglitazone therapy was associated with significant reductions compared with placebo in HbA(1c) (between-treatment difference in least squares [LS] mean change from baseline. -0.70 %; 95 % CI, -0.85 to -0.54; P < 0.001) and FPG (-17.7 mg/dL; 95% CI, -24.3 to -11.0; P < 0.001). Mean HbA(1c) values at end point were 7.2% (0.9) and 7.8% (1.1) in the respective treatment groups, and the proportions of patients reaching a target HbA(1c) of <7.0% were 45.4% and 23.0% (P < 0.001). Significant reductions in fasting serum proinsulin levels and the proinsulin/insulin ratio were seen with sitagliptin treatment compared with placebo (both, P < 0.01). Sitagliptin was generally well tolerated, with no increased risk of hypoglycemia compared with placebo (2 vs 0 patients, respectively).

Aged↗

PubMed2005

Comparison between two partial likelihood approaches for the competing risks model with missing cause of failure.

In many clinical studies where time to failure is of primary interest, patients may fail or die from one of many causes where failure time can be right censored. In some circumstances, it might also be the case that patients are known to die but the cause of death information is not available for some patients. Under the assumption that cause of death is missing at random, we compare the Goetgbebeur and Ryan (1995, Biometrika, 82, 821-833) partial likelihood approach with the Dewanji (1992, Biometrika, 79, 855-857) partial likelihood approach. We show that the estimator for the regression coefficients based on the Dewanji partial likelihood is not only consistent and asymptotically normal, but also semiparametric efficient. While the Goetghebeur and Ryan estimator is more robust than the Dewanji partial likelihood estimator against misspecification of proportional baseline hazards, the Dewanji partial likelihood estimator allows the probability of missing cause of failure to depend on covariate information without the need to model the missingness mechanism. Tests for proportional baseline hazards are also suggested and a robust variance estimator is derived.

Cause of Death↗