scispace - formally typeset
M

Martina Mueller-Nurasyid

Researcher at Ludwig Maximilian University of Munich

Publications -  33
Citations -  9920

Martina Mueller-Nurasyid is an academic researcher from Ludwig Maximilian University of Munich. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 18, co-authored 33 publications receiving 8394 citations. Previous affiliations of Martina Mueller-Nurasyid include University of Porto.

Papers
More filters
Journal ArticleDOI

Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 19.2 million participants

Mariachiara Di Cesare, +741 more
- 02 Apr 2016 - 
TL;DR: The posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue, is calculated.
Journal ArticleDOI

Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants

Bin Zhou, +497 more
- 09 Apr 2016 - 
TL;DR: In this article, the authors used a Bayesian hierarchical model to estimate trends in diabetes prevalence, defined as fasting plasma glucose of 7.0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs in 200 countries and territories in 21 regions, by sex and from 1980 to 2014.

The genetic architecture of type 2 diabetes

Christian Fuchsberger, +300 more
TL;DR: Large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes, but most fell within regions previously identified by genome-wide association studies.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Sonja I. Berndt, +321 more

Rare and low-frequency coding variants alter human adult height

Eirini Marouli, +370 more
TL;DR: The results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.