TITLE:
On Heredity Factors of Parkinson’s Disease: A Parametric and Bayesian Analysis
AUTHORS:
Abolfazl Saghafi, Chris P. Tsokos, Rebecca D. Wooten
KEYWORDS:
Parkinson’s Disease, Heredity, Bayesian Estimation, Maximum Likelihood, Statistical Modelling
JOURNAL NAME:
Advances in Parkinson's Disease,
Vol.7 No.3,
August
31,
2018
ABSTRACT: Hereditary
is one of the key risk factors of the Parkinson’s disease (PD) and children of
individuals with the Parkinson’s carry a two-fold risk for the disease. In this
article, chance of developing the Parkinson’s disease is estimated for an
individual in five types of families. That is, families with negative history
of the PD (I), families with positive history where neither one of the parents
(II), one of the parents (III-IV), or both parents (V) are diagnosed with the
disease. After a sophisticated modeling, Maximum Likelihood and Bayesian Approach
are used to estimate the chance of developing the Parkinson’s in the five
mentioned family types. It is extremely important knowing such probabilities as
the individual can take precautionary measures to defy the odds. While many
physicians have provided medical opinions on chance of developing the PD, our
study is one of the first to provide statistical modeling and analysis with real
data to support the conclusions.