Christoph Lange, Ph.D.

Professor of Biostatistics at the Harvard School of Public Health

Assistant Professor of Medicine in the Channing Division of Medicine at Brigham and Women’s Hospital and Harvard Medical School

I am a Professor of Biostatistics at the Harvard School of Public Health, with a joint appointment as an Assistant Professor of Medicine in the Channing Division of Medicine at Brigham and Women’s Hospital and Harvard Medical School. I am an expert in many areas of statistical genetics, with particular expertise derived from my knowledge of family-based association designs and the development and application of methods utilizing family-based association testing in studies using genome-wide association data and sequence analysis. I am a frequent collaborator of investigators in Alzheimer's genetics and the Systems Genetics and Genomics Unit (SGGU) of the Channing Division of Network Medicine. I have served as a senior biostatistician on several large, ongoing Alzheimer's Disease and SGGU projects which are focused on asthma and COPD genetics and epidemiology. I work with some of the most productive and innovative researchers in the field of causal inference and mediation, which allowed me to analyze the causal relationship in associations of genetic determinants with lung cancer and smoking behavior. In addition to this work in lung phenotypes, I also have long-standing expertise in statistical genetics and epidemiology of mental health phenotypes. As a faculty member, I have mentored over 10 post-doctoral fellows and have been the primary thesis and research advisor to 9 pre-doctoral students and Ph.D. candidates.

Funded Research

Project Description Researchers Funding
Analytical and Statistical Tools for Sequence Analysis for Alzheimer's Disease

The availability of next generation sequencing data in large scale association studies for Alzheimer’s disease provides a unique research opportunity. The data contains the information that is required to identify causal disease susceptibility loci (DSL) for Alzheimer’s disease and many other mental health phenotypes and psychiatric diseases. In order to translate the wealth of information into DSL discovery for Alzheimer’s disease, powerful statistical methodology is required. So far, a large number of rare variant association tests have been proposed.

2015 to 2016


Selected Publications

These published papers resulted from Cure Alzheimer’s Fund support.
Heide Loehlein Fier, Dmitry Prokopenko, Julian Hecker, Michael H. Cho, Edwin K. Silverman, Scott T. Weiss, Rudolph E. Tanzi, Christoph Lange, On the association analysis of genome-sequencing data: A spatial clustering approach for partitioning the entire genome into nonoverlapping windows, Genetic Epidemiology, 41(4), 20 Mar 2017, 332–340
C Herold, B V Hooli, K Mullin, T Liu, J T Roehr, M Mattheisen, A R Parrado, L Bertram, C Lange and R E Tanzi, Family-based association analyses of imputed genotypes reveal genome-wide significant association of Alzheimer’s disease with OSBPL6, PTPRG, and PDCL3, Molecular Psychiatry, February 2016
Dmitry Prokopenko , Julian Hecker, Edwin Silverman, Markus M. Nöthen, Matthias Schmid, Christoph Lange, Heide Loehlein Fier, Using Network Methodology to Infer Population Substructure, Plos, June 22, 2015