Table 2. Salient motivating factors in choosing to model a disease with human iPSC technology.

For the disease categories listed in each row, the salient characteristics of each are highlighted in relation to the technical challenges of creating disease hiPSC models. This table is meant to be illustrative of different challenges facing several types of disease, and not an exhaustive list of hiPSC models. For example, in infectious diseases (e.g., HIV), a humanized mouse model with hiPSCs could explore human host factors that confer resistance. Three motivating factors for using hiPSC technology to model a disease are anticipated to be important for each class of diseases (denoted by green “+”). First, the genetics of the disease may be an important factor. On the one hand, if disease etiology is expected to involve many genetic lesions across the human genome, the hiPSC technology can provide a cell line which contains the appropriate disease-relevant combinations of these lesions. On the other hand, clear Mendelian genetics enables one to be certain that the genetic lesion is captured in the hiPS-derived cells. Second, if animal models could not reasonably be expected to recapitulate disease pathology or phenotype (most particularly for psychiatric/neurobehavioral disease), hiPSC-derived cells may be the best option to study the cellular changes involved in a particular diseases. Third, where there is well-characterized pathology in human diseases, phenotypes observed in hiPSC derivatives can be more easily related to those seen in patients. Two potential complicating factors are denoted by a red “+”. Non-cell autonomous pathology will likely be difficult to model with differentiated hiPSC cell types, and environmental stresses may be difficult to recapitulate experimentally. If disease-specific hiPSCs have been derived from particular patient groups, the references are listed on the right most column.

Disease Categories			Motivating Factors				Potential Complicating Factors			Existing hiPSC Line
			Multifactorial genetics	Human- specific pathology	Molecular & histopathology well- characterized	Other	Non-cell autonomous pathology	Environmental stresses	Other
Neurology	Neurodegenerative	Familial	?	+	+	Mendelian genetics in many cases	+	?	Early onset in some cases; Network dysfunction likely important	Huntington’s disease (Park et al., 2008b); dysautonomia (Lee et al., 2009); SMA type 1 (Ebert et al., 2009); ALS (Dimos et al., 2008)
		Sporadic	+	+	+	Cellular pathology well- defined	+	+	Network dysfunction likely important	Parkinson’s disease (Park et al., 2008b; Soldner et al., 2009)
	Neuro- developmental		+ in some cases	+	+	Well-defined genetic lesions in many cases	+	?	Complex phenotypes involving many parts of the body; Network dysfunction likely important	Rett Syndrome (Hotta et al., 2009); Down Syndrome (Park et al., 2008b)
	Neurobehavioral/Psychological		+	+	?	Opportunity to define cellular pathology	+	+	Network dysfunction likely important	None published
Hematology/Oncology			+	+	+	Well-defined genetic lesions in some cases; Correct known genetic defects readily via bone- marrow manipulation; Opportunity to distinguish epigenetic & genetic factors	?	+ in some cases	Assaying function of hematopoietic derivatives;iPSC state may erase important epigenetic alterations	Sickle-cell disease (Ye et al., 2009a); Fanconi anemia (Raya et al., 2009); Myeloproliferative disorders (Ye et al., 2009b)
Endocrinology			+	?	+	Well-defined cellular pathology; sometimes well- defined genetic lesions	+	+	Autoimmune response likely important	Juvenile diabetes mellitus (Maehr et al., 2009; Park et al., 2008b)
Infectious diseases			+	+	?	Amenable to reverse genetics to look for host susceptibility factors	?	?	Susceptibility could rely on specific aspects of physiology	None published